* fix(ingestion): reduce parse-phase memory for huge repos (#1983)
Stop retaining full parse-cache chunks in RAM alongside the merged graph,
slim on-disk shards, defer worker ParsedFile emission for scope-resolver
languages, and add GITNEXUS_DEBUG_HEAP probes for OOM diagnosis.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(ingestion): address #2038 tri-review findings (parse-phase memory)
Resolves the confirmed review findings on PR #2038:
- P1: thread exportedTypeMap through the sequential parse path
(processParsingSequential) so a no-worker run over a partially-warm
cache no longer silently drops the sequential-miss files' exported
types. Cache hits made exportedTypeMap.size > 0, suppressing the
end-of-loop buildExportedTypeMapFromGraph rebuild, but the sequential
path never populated the map. Regression test added (fails on the
pre-fix tree, passes after) plus a fully-sequential differential oracle.
- P2: saveParseCache builds its on-disk index from hashes actually
written/copied (writtenKeys), never a usedKeys hash whose shard write
or copy was skipped — no more phantom index entries.
- P2: add a unit test asserting SCOPE_RESOLUTION_LANGUAGES stays in sync
with SCOPE_RESOLVERS (asymmetric drift would lose a language's ParsedFile).
- Backfill cache coverage: loadParseCacheChunk missing/corrupt -> undefined,
pruneCache onDiskKeys branch, slim preserves nodes, saveParseCache
copy-evicted-shard round-trip.
- Cleanups: single-source heap-probe gating via isDebugHeapEnabled();
hoist the per-chunk mkdir in persistParseCacheChunk behind a
process-scoped Set; gate COBOL's unused worker-side ParsedFile
extraction (graph nodes still come from cobolPhase) while keeping
fileCount/progress unconditional.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor(ingestion): remove dead worker-side ParsedFile extraction
After #2038 gated worker `ParsedFile` emission behind `!isScopeResolutionLanguage(language)`, and with all 16 SupportedLanguages registered in SCOPE_RESOLVERS, that gate was structurally always true — the worker already produced no ParsedFiles and scope-resolution re-extracts each file from source on the main thread (run.ts). Remove the now-dead machinery:
- Drop both worker `extractParsedFile` call-sites (tree-sitter processFileGroup + the standalone-provider branch) and the `result.parsedFiles.push`. The standalone branch keeps fileCount/onFileProcessed per file. `result.parsedFiles` stays declared but empty (field removal deferred).
- Remove the now-orphaned `scopeSourceKind` var + `ScopeCaptureSourceKind`/`extractParsedFile`/`isScopeResolutionLanguage` imports.
- Delete the consumerless `migrated-languages.ts` (isScopeResolutionLanguage + SCOPE_RESOLUTION_LANGUAGES) and its drift-guard test — parse-worker was their only importer. Also improves AGENTS.md "shared ingestion code must not name languages" compliance.
`extractParsedFile` and the scope-extractor-bridge stay (scope-resolution/run.ts + Vue resolver use them). Behavior-preserving: worker-sequential-parity passes before and after; tsc/eslint clean; no baseline/golden drift.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor(ingestion): worker-pool-only parsing; remove sequential parser (#1983)
Completes the #1983 huge-repo parse-OOM effort by making the worker pool
GitNexus's sole parse path.
Parallel serialization (the perf core): workers serialize their ParsedFiles to
a disk store in parallel and stream them back to scope-resolution, so the main
thread no longer re-parses every file (the tree-sitter native-memory leak that
caused the OOM). Adds chunk merge-pipelining + work-proportional chunk sizing so
the pool stays saturated.
Remove the sequential parser: `--workers 0`, `GITNEXUS_WORKER_POOL_SIZE=0`, and
`skipWorkers` now hard-error (no silent degrade — #1741); the small-repo
threshold no longer selects an in-process path; pool creation stays lazy /
cache-miss-gated so warm all-hit runs never spawn workers.
Worker-path parity fixes — removing sequential surfaced two pre-existing gaps
that tiny-fixture tests had masked by running below the worker threshold, both
fixed by carrying per-file metadata as DATA across the worker boundary (never
re-parsing on the main thread, preserving the OOM fix):
- C++: templateConstraints wired into worker node identity (SFINAE overload
disambiguation) + ADL / inline-namespace capture side-channel serialized
onto the ParsedFile.
- Kotlin: companion-scope side-channel serialized the same way (companion /
static dispatch).
Validation: tsc + build clean; full suite green (10,190 pass — the only
deterministic failures were the now-fixed C++/Kotlin worker-path gaps; the 2
remaining full-run failures are pre-existing load flakiness, green in
isolation); cpp-pipeline benchmark stays linear on a 1-worker pool.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(ingestion): wire C static-linkage side-channel + ADL O(1) collect + tri-review cleanups (#1983)
Follow-up to the worker-pool-only refactor, from a tri-review of the parse path.
- C static-linkage side-channel (P1): cProvider had no collect/applyCaptureSideChannel,
so on the now-sole worker path C `static` file-local marks were lost across the worker
boundary -> false cross-file CALLS edges + over-broad #include wildcard visibility on
every C analysis (the Linux kernel is C). Mirror the C++/Kotlin wiring: serialize
`staticNames` per file onto ParsedFile.captureSideChannel and restore it on the main
thread (no re-parse). + a worker-path regression test (the existing c-static-isolation
fixture passed vacuously — its collision resolves via #include before the global
free-call fallback ever consults static-linkage).
- captureSideChannel `kind` discriminant: add `kind:'cpp'`/`kind:'c'` tags + guards
(Kotlin already had one) now that C/C++/Kotlin share the single generic field.
- Perf: collectCppAdlSideChannel scanned the whole argInfoBySite/noAdlSites maps per file
(O(F^2) per sub-batch, ~100M parseSiteKey calls at kernel scale). Add per-filePath
lockstep indexes -> O(1) collect; serialized snapshot byte-identical.
- Cleanups: inline the one-line processParsingWithWorkers wrapper into processParsing;
drop the always-empty WorkerExtractedData.calls/assignments/constructorBindings fields;
remove the voided astCache param from processParsing; refresh stale "sequential
fallback" JSDoc.
Validation: tsc + build clean; cpp 297/297, c 8/8 (incl. the new worker-path
static-linkage guard), typescript + parsedfile-store green; cpp ADL benchmark stays linear.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* perf(scope-resolution): index C/C++ #include resolution in finalize (O(n²)→O(n))
Kernel-scale C/C++ analysis ground in finalizeScopeModel because three
per-#include operations each did a full O(F) scan with no index — the
finalize O(n²) that surfaced once the #1983 parse-phase OOM was fixed:
- expand{C,Cpp}WildcardNames: parsedFiles.find() per wildcard edge → O(R·F)
- resolveImportTarget: new Set(allFilePaths) rebuilt per #include
- resolveCImportTarget: suffix-match scanned all workspace paths
Each is replaced with a WeakMap-per-pass index keyed on the stable
parsedFiles/allFilePaths references that scope-resolution run.ts passes
once per pass:
- Map<ScopeId,ParsedFile> for wildcard expansion (c/static-linkage.ts +
cpp/file-local-linkage.ts)
- memoized augmented header set (c/scope-resolver.ts + cpp/scope-resolver.ts)
- basename-bucketed suffix index in resolveCImportTarget (c/import-target.ts),
shared by C and C++ since resolveCppImportTarget delegates to it
Collapses the C/C++ finalize from O(R·F) to O(R+F). Pure-perf, byte-identical
edge output: 962 targeted tests green (490 C + 472 C/C++ scope-resolution);
the basename index preserves the exact endsWith('/'+target) match and the
fewest-path-components-then-lexicographic tie-break.
The kernel's ~25-30k .h headers are classified C++, so both providers must
be fixed. Proven on the Linux kernel: the C finalize completed
(sr-post-finalize lang=c → sr-end lang=c), which the pre-fix run never
reached in 16+ min of grinding.
Build-independent follow-ups (separate from this finalize fix), documented
for later: emitFreeCallFallback same-name buckets (emit phase),
buildGraphNodeLookup + precount global setup, the ParsedFile store-load,
the dart/go/ruby expand-wildcards .find siblings, and the ~26GB
scope-resolution memory floor (full kernel completion needs >~40GB RAM).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test(bench): regenerate C scope-capture baseline for the #1983 c-static-linkage-worker fixture
bench/scope-capture/measure.mjs fingerprints emitCScopeCaptures over the
lang-resolution/c-* fixture corpus. The #1983 PR added the
c-static-linkage-worker fixture (caller.c/lib.c/lib.h/local.c — the
worker-path static-linkage side-channel test) but did not regenerate the C
baseline, so `--check` has been red on this branch (main, lacking the
fixture, still matches 0de009b).
Pure fixture-corpus drift — no c/captures.ts or query change branch-vs-main,
existing fixtures' captures byte-identical (c-captures.test.ts 45/45),
scaling stays linear (~0.97). Regenerated: 0de009b -> 39f3a83. Bench now
PASS (14 languages). Unrelated to the finalize O(n²) fix.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* perf(scope-resolution): lower kernel-scale resident memory floor + setup cost
Reduce the scope-resolution resident-memory floor and setup throughput on
huge repos (Linux kernel), the wall that remains after #1983 (parse OOM) and
the finalize O(n^2) fix (
|
||
|---|---|---|
| .claude | ||
| .claude-plugin | ||
| .cursor | ||
| .devcontainer | ||
| .gemini/commands | ||
| .github | ||
| .history/gitnexus | ||
| .husky | ||
| .sisyphus/drafts | ||
| deploy/kubernetes | ||
| eslint-rules | ||
| eval | ||
| gitnexus | ||
| gitnexus-claude-plugin | ||
| gitnexus-cursor-integration | ||
| gitnexus-shared | ||
| gitnexus-test-setup | ||
| gitnexus-web | ||
| pr-swarm-review | ||
| .cursorrules | ||
| .dockerignore | ||
| .env.example | ||
| .git-blame-ignore-revs | ||
| .gitattributes | ||
| .gitignore | ||
| .gitleaks.toml | ||
| .mcp.json | ||
| .prettierignore | ||
| .prettierrc | ||
| .windsurfrules | ||
| AGENTS.md | ||
| ARCHITECTURE.md | ||
| CHANGELOG.md | ||
| CLAUDE.md | ||
| compound-engineering.local.md | ||
| CONTRIBUTING.md | ||
| docker-compose.yaml | ||
| docker-server.mjs | ||
| docker-server.test.mjs | ||
| Dockerfile.cli | ||
| Dockerfile.web | ||
| DoD.md | ||
| eslint.config.mjs | ||
| GUARDRAILS.md | ||
| LICENSE | ||
| llms.txt | ||
| MIGRATION.md | ||
| package-lock.json | ||
| package.json | ||
| README.md | ||
| RUNBOOK.md | ||
| SECURITY.md | ||
| skills.mdm | ||
| swift-ingestion-gaps.md | ||
| TESTING.md | ||
| type-resolution-roadmap.md | ||
| type-resolution-system.md | ||
GitNexus
⚠️ Important Notice: GitNexus has NO official cryptocurrency, token, or coin. Any token/coin using the GitNexus name on Pump.fun or any other platform is not affiliated with, endorsed by, or created by this project or its maintainers. Do not purchase any cryptocurrency claiming association with GitNexus.
Join the official Discord to discuss ideas, issues etc!
Enterprise (SaaS & Self-hosted) - akonlabs.com
Building nervous system for agent context.
Indexes any codebase into a knowledge graph — every dependency, call chain, cluster, and execution flow — then exposes it through smart tools so AI agents never miss code.
https://github.com/user-attachments/assets/172685ba-8e54-4ea7-9ad1-e31a3398da72
Like DeepWiki, but deeper. DeepWiki helps you understand code. GitNexus lets you analyze it — because a knowledge graph tracks every relationship, not just descriptions.
TL;DR: The Web UI is a quick way to chat with any repo. The CLI + MCP is how you make your AI agent actually reliable — it gives Cursor, Claude Code, Antigravity, Codex, and friends a deep architectural view of your codebase so they stop missing dependencies, breaking call chains, and shipping blind edits. Even smaller models get full architectural clarity, making it compete with Goliath models.
Star History
Two Ways to Use GitNexus
| CLI + MCP | Web UI | |
|---|---|---|
| What | Index repos locally, connect AI agents via MCP | Visual graph explorer + AI chat in browser |
| For | Daily development with Cursor, Claude Code, Antigravity, Codex, Windsurf, OpenCode | Quick exploration, demos, one-off analysis |
| Scale | Full repos, any size | Limited by browser memory (~5k files), or unlimited via backend mode |
| Install | npm install -g gitnexus |
No install — gitnexus.vercel.app |
| Storage | LadybugDB native (fast, persistent) | LadybugDB WASM (in-memory, per session) |
| Parsing | Tree-sitter native bindings | Tree-sitter WASM |
| Privacy | Everything local, no network | Everything in-browser, no server |
Bridge mode:
gitnexus serveconnects the two — the web UI auto-detects the local server and can browse all your CLI-indexed repos without re-uploading or re-indexing.
Enterprise
GitNexus is available as an enterprise offering - either as a fully managed SaaS or a self-hosted deployment. Also available for commercial use of the OSS version with proper licensing.
Enterprise includes:
- PR Review - automated blast radius analysis on pull requests
- Auto-updating Code Wiki - always up-to-date documentation (Code Wiki is also available in OSS)
- Auto-reindexing - knowledge graph stays fresh automatically
- Multi-repo support - unified graph across repositories
- OCaml support - additional language coverage
- Priority feature/language support - request new languages or features
Upcoming:
- Auto regression forensics
- End-to-end test generation
👉 Learn more at akonlabs.com
💬 For commercial licensing or enterprise inquiries, ping us on Discord or drop an email at founders@akonlabs.com
Development
- ARCHITECTURE.md — packages, index → graph → MCP flow, where to change code
- RUNBOOK.md — analyze, embeddings, stale index, MCP recovery, CI snippets
- GUARDRAILS.md — safety rules and operational “Signs” for contributors and agents
- CONTRIBUTING.md — license, setup, commits, and pull requests
- TESTING.md — test commands for
gitnexusandgitnexus-web
CLI + MCP (recommended)
The CLI indexes your repository and runs an MCP server that gives AI agents deep codebase awareness.
Quick Start
# Index your repo (run from repo root)
npx gitnexus analyze
That's it. This indexes the codebase, installs agent skills, registers Claude Code hooks, and creates AGENTS.md / CLAUDE.md context files — all in one command.
On npm 11.x?
npxcan crash during install withCannot destructure property 'package' of 'node.target'(an npm/arborist bug, before GitNexus runs). Use pnpm instead — it builds the native deps explicitly:pnpm --allow-build=@ladybugdb/core --allow-build=gitnexus --allow-build=tree-sitter dlx gitnexus@latest analyzeOr install globally (
npm install -g gitnexus@latest) and rungitnexus analyze. See #1939.
To configure MCP for your editor, run npx gitnexus setup once — or set it up manually below.
Faster install (no C++ toolchain needed): set
GITNEXUS_SKIP_OPTIONAL_GRAMMARS=1beforenpm install -g gitnexusto skip vendored grammar materialize/build (tree-sitter-dart,tree-sitter-proto,tree-sitter-swift). Dart/Proto/Swift files won't be parsed, but install completes in seconds withoutpython3/make/g++. Strict=1only — any other value falls through to the rebuild.
MCP Setup
gitnexus setup auto-detects your editors and writes the correct global MCP config. You only need to run it once.
Editor Support
| Editor | MCP | Skills | Hooks (auto-augment) | Support |
|---|---|---|---|---|
| Claude Code | Yes | Yes | Yes (PreToolUse + PostToolUse) | Full |
| Cursor | Yes | Yes | Yes (postToolUse, manual install) | Full |
| Antigravity (Google) | Yes | Yes | Yes (AfterTool, Gemini CLI hooks schema)¹ | Full |
| Codex | Yes | Yes | — | MCP + Skills |
| Windsurf | Yes | — | — | MCP |
| OpenCode | Yes | Yes | — | MCP + Skills |
Claude Code gets the deepest integration: MCP tools + agent skills + PreToolUse hooks that enrich searches with graph context + PostToolUse hooks that detect a stale index after commits and prompt the agent to reindex.
¹ Antigravity hooks follow the Gemini CLI hooks reference (Antigravity 2.0 is the documented successor to Gemini CLI). Augmentation runs in
AfterToolbecauseBeforeToolhas no context-injection channel in the Gemini contract — the agent sees graph context appended to the tool result viahookSpecificOutput.additionalContext. Stale-index hints land in the same channel after a successfulgit commit/merge/rebase/cherry-pick/pull. The schema may evolve if Antigravity-specific hook docs diverge from Gemini CLI's; the implementation will track those changes.
Community Integrations
Built by the community — not officially maintained, but worth checking out.
| Project | Author | Description |
|---|---|---|
| pi-gitnexus | @tintinweb | GitNexus plugin for pi — pi install npm:pi-gitnexus |
| gitnexus-stable-ops | @ShunsukeHayashi | Stable ops & deployment workflows (Miyabi ecosystem) |
Have a project built on GitNexus? Open a PR to add it here!
If you prefer manual configuration:
Recommended for fastest startup: install gitnexus globally (
npm i -g gitnexus) and rungitnexus setup— this writes an absolute-path MCP config that bypassesnpxentirely. The pinned-npxsnippets below are a quickstart fallback; on a cold cache thenpxinstall can exceed Claude Code'sMCP_TIMEOUTdefault (~30s).
Claude Code (full support — MCP + skills + hooks):
# macOS / Linux
claude mcp add gitnexus -- npx -y gitnexus@latest mcp
# Windows
claude mcp add gitnexus -- cmd /c npx -y gitnexus@latest mcp
Codex (full support — MCP + skills):
codex mcp add gitnexus -- npx -y gitnexus@latest mcp
Cursor (~/.cursor/mcp.json — global, works for all projects):
{
"mcpServers": {
"gitnexus": {
"command": "npx",
"args": ["-y", "gitnexus@latest", "mcp"]
}
}
}
Antigravity (Google) — ~/.gemini/antigravity/mcp_config.json:
{
"mcpServers": {
"gitnexus": {
"command": "npx",
"args": ["-y", "gitnexus@latest", "mcp"]
}
}
}
gitnexus setupalso merges anAfterToolentry into~/.gemini/settings.json(under the canonical Gemini CLI hooks schema) and installs skills to~/.gemini/antigravity/skills/. Existing user hooks are preserved. The hook adapter's path is rewritten at install time, so rungitnexus setuprather than hand-editing.
OpenCode (~/.config/opencode/config.json):
{
"mcp": {
"gitnexus": {
"type": "local",
"command": ["gitnexus", "mcp"]
}
}
}
Codex (~/.codex/config.toml for system scope, or .codex/config.toml for project scope):
[mcp_servers.gitnexus]
command = "npx"
args = ["-y", "gitnexus@latest", "mcp"]
CLI Commands
gitnexus setup # Configure MCP for your editors (one-time)
gitnexus analyze [path] # Index a repository (or update stale index)
gitnexus analyze --repair-fts # Fast path: rebuild/verify only FTS indexes on existing index data
gitnexus analyze --force # Full rebuild: re-parse + graph rebuild + FTS rebuild
gitnexus analyze --skills # Generate repo-specific skill files from detected communities
gitnexus analyze --skip-embeddings # Skip embedding generation (faster)
gitnexus analyze --skip-agents-md # Preserve custom AGENTS.md/CLAUDE.md gitnexus section edits
gitnexus analyze --skip-skills # Skip installing .claude/skills/gitnexus/ skill files
gitnexus analyze --default-branch develop # Branch used in the generated regression-compare example (base_ref)
gitnexus analyze --skip-git # Index folders that are not Git repositories
gitnexus analyze --embeddings [limit] # Enable embedding generation (slower, better search)
gitnexus analyze --verbose # Log skipped files when parsers are unavailable
gitnexus analyze --worker-timeout 60 # Increase worker idle timeout for slow parses
gitnexus analyze --wal-checkpoint-threshold 67108864 # 64 MiB. Control LadybugDB WAL auto-checkpoint threshold (default: 67108864 = 64 MiB; -1 keeps Ladybug stock ~16 MiB)
gitnexus analyze --workers <n> # Parse worker pool size (default: cores-1, capped at 16; 0 = sequential)
gitnexus mcp # Start MCP server (stdio) — serves all indexed repos
gitnexus serve # Start local HTTP server (multi-repo) for web UI connection
gitnexus list # List all indexed repositories
gitnexus status # Show index status for current repo
gitnexus clean # Delete index for current repo
gitnexus clean --all --force # Delete all indexes
gitnexus wiki [path] # Generate repository wiki from knowledge graph
gitnexus wiki --model <model> # Wiki with custom LLM model (default: gpt-4o-mini)
gitnexus wiki --base-url <url> # Wiki with custom LLM API base URL
gitnexus publish # Notify the understand-quickly registry (opt-in, see below)
# Repository groups (multi-repo / monorepo service tracking)
gitnexus group create <name> # Create a repository group
gitnexus group add <group> <groupPath> <registryName> # Add a repo to a group. <groupPath> is a hierarchy path (e.g. hr/hiring/backend); <registryName> is the repo's name from the registry (see `gitnexus list`)
gitnexus group remove <group> <groupPath> # Remove a repo from a group by its hierarchy path
gitnexus group list [name] # List groups, or show one group's config
gitnexus group sync <name> # Extract contracts and match across repos/services
gitnexus group contracts <name> # Inspect extracted contracts and cross-links
gitnexus group query <name> <q> # Search execution flows across all repos in a group
gitnexus group status <name> # Check staleness of repos in a group
If analyze reports a worker parse timeout on a large or unusual repository, it keeps running and falls back safely. To give slow worker jobs more time, use gitnexus analyze --worker-timeout 60 or set GITNEXUS_WORKER_SUB_BATCH_TIMEOUT_MS=60000. For very large files, GITNEXUS_WORKER_SUB_BATCH_MAX_BYTES controls the worker job byte budget.
Embeddings node limit
gitnexus analyze --embeddings generates semantic search vectors with a default 50,000-node safety cap to protect memory on large repositories. Override the cap when you know the host has enough memory for a larger graph, or disable it entirely for a one-off full embeddings run.
# Generate embeddings with the default 50,000 node safety cap
gitnexus analyze --embeddings
# Disable the safety cap entirely
gitnexus analyze --embeddings 0
# Use a custom cap
gitnexus analyze --embeddings 100000
If embeddings are skipped on a large repository, the indexed graph likely exceeds the default safety cap. Re-run with gitnexus analyze --embeddings 0 to remove the cap, or gitnexus analyze --embeddings <n> to choose a higher limit while still keeping memory bounded.
Project config (.gitnexusrc)
Commit a .gitnexusrc JSON file at the repo root to preconfigure recurring analyze options per project, instead of re-passing the same flags every run. It is read from the resolved repo root (not .gitnexus/, which is gitignored index storage). CLI flags always override .gitnexusrc.
{
// Default branch used in the generated regression-compare example (base_ref).
// Use this so a project on `develop`/`master` doesn't get "main" rewritten
// over its fix on every analyze. (Alias: "branch".)
"defaultBranch": "develop",
"skipContextFiles": true, // alias of skipAgentsMd: keep your own AGENTS.md/CLAUDE.md
"skipSkills": true, // don't install .claude/skills/gitnexus/
"embeddings": true, // generate embeddings by default
"workerTimeout": 60
}
A nested analyze block is also accepted (and overrides flat keys for the same option):
{ "analyze": { "defaultBranch": "develop", "skipSkills": true } }
Notes:
- The default branch is resolved as:
--default-branch>.gitnexusrcdefaultBranch/branch> auto-detectedorigin/HEAD>main. skipContextFiles/skipAiContextare aliases forskipAgentsMd— they skip theAGENTS.md/CLAUDE.mdblock only. They do not implyskipSkills.indexOnlyis the stronger option that skips all file injection.- Supported keys:
defaultBranch(branch),skipAgentsMd(skipContextFiles,skipAiContext),skipSkills,indexOnly,stats/noStats,embeddings,dropEmbeddings,name,allowDuplicateName,maxFileSize,workerTimeout,walCheckpointThreshold,workers,embeddingThreads,embeddingBatchSize,embeddingSubBatchSize,embeddingDevice. - The file is JSON only. Unknown keys and invalid values fail fast with an actionable error before analysis starts.
Environment variables
Most analyze knobs are also CLI flags (--workers, --worker-timeout, --max-file-size, --verbose). Use the env-var form when you'd otherwise repeat the same flag every run, or when invoking GitNexus from a long-running host (MCP server, eval-server, CI shell) that already manages its own environment. CLI flags take precedence over env vars; env vars take precedence over built-in defaults.
| Variable | Default | Effect | Tune when… |
|---|---|---|---|
GITNEXUS_WORKER_POOL_SIZE |
cores - 1, capped at 16 |
Parse worker pool size. 0 disables the pool (sequential fallback). Equivalent to --workers <n>. |
Constrained containers (cgroup CPU limits), CI runners with explicit quotas, or debugging a worker-only crash via 0. |
GITNEXUS_PARSE_CHUNK_CONCURRENCY |
2 |
Number of chunks whose file contents may be read into memory in parallel while the pool dispatches the current chunk. Worker dispatch itself stays serial. | Repos large enough to chunk (multi-MB total source) where disk I/O is a measurable fraction of analyze wall-clock. |
GITNEXUS_VERBOSE |
unset | When 1, enables verbose ingestion logs (skipped-file warnings, per-chunk throughput, parse-cache stats). Equivalent to --verbose. |
Debugging an analyze that "completed" but seems to have missed files; tuning --workers / chunk concurrency against observable throughput. |
GITNEXUS_PROFILE_DEFERRED |
unset | When 1, emits [deferred-profile] timing/progress logs for the post-chunk deferred resolution band (imports → heritage → buildHeritageMap → legacy call resolution). Implied by GITNEXUS_VERBOSE. |
Diagnosing analyze stalls in "Resolving calls (all chunks)" on large Java/Kotlin repos (issue #1741) without the full verbose ingestion noise. |
GITNEXUS_PROFILE_DEFERRED_SLOW_MS |
3000 (verbose) / 5000 |
Per-file threshold in ms above which processCallsFromExtracted emits a slow file … log line. Parsed via Number(): accepts integers (5000), scientific notation (2.5e3), decimals (.5), and hex (0x10). Non-finite or non-positive values fall back to the default. |
Hunting a few outlier files dominating the deferred call-resolution stage; lower to surface more, raise to focus only on the worst. |
GITNEXUS_MAX_FILE_SIZE |
512 (KB) |
Walker skip threshold in KB. Hard cap is 32768 (tree-sitter buffer ceiling). Equivalent to --max-file-size <kb>. |
Indexing repos with intentionally-large source files (generated parsers, vendored bundles) that should still be parsed. |
GITNEXUS_WORKER_SUB_BATCH_TIMEOUT_MS |
30000 |
Worker idle timeout in milliseconds before retry/fallback. Equivalent to --worker-timeout <seconds> × 1000. |
Slow-parsing files (large minified JS, deeply-nested TS types) that legitimately need more than 30s. |
GITNEXUS_WAL_CHECKPOINT_THRESHOLD |
67108864 (64 MiB) |
LadybugDB WAL auto-checkpoint threshold in bytes. Equivalent to --wal-checkpoint-threshold <bytes>. -1 keeps LadybugDB's stock threshold (~16 MiB). Larger thresholds reduce checkpoint frequency but increase the WAL size at rotation time — choose a smaller value on disk-constrained environments. |
You need a larger or smaller WAL auto-checkpoint threshold for your analyze workload. |
GITNEXUS_WORKER_SUB_BATCH_MAX_BYTES |
8388608 (8 MB) |
Per-job byte budget the pool will send to a worker in one postMessage. |
Very large individual files; mostly diagnostic — bumping past 8 MB risks structured-clone memory pressure. |
GITNEXUS_WORKER_MAX_RESPAWNS_PER_SLOT |
3 |
Max replacement spawns per worker slot before the slot is dropped from the active rotation. Bounds respawn loops on a chronically-crashing slot. | Hosts where a flaky worker should retry more (raise) or fail-fast (lower) before the slot is dropped. |
GITNEXUS_WORKER_MAX_CUMULATIVE_TIMEOUT_MS |
5 × subBatchTimeoutMs |
Total retry wall-time budget per job before quarantining. Combined with timeoutBackoffFactor, prevents exponentially-growing retries from stalling for hours. |
Slow files that legitimately need long total retry windows; lower to fail-fast on stalls. |
GITNEXUS_WORKER_CONSECUTIVE_FAILURE_THRESHOLD |
max(3, poolSize) |
Per-slot consecutive deaths before the pool's circuit breaker trips. After tripping, every subsequent dispatch rejects until a fresh pool is created. | Hosts where a SIGSEGV-prone native grammar should trip the breaker sooner; CI runners that should fail loudly. |
GITNEXUS_CHUNK_BYTE_BUDGET |
2097152 (2 MB) |
Chunk boundary used for cache-key composition and dispatch. Smaller = finer-grained cache hits but more dispatch overhead. | Tuning incremental-analyze cache behavior on monorepos. |
GITNEXUS_NO_GITIGNORE |
unset | When set, skips .gitignore parsing. .gitnexusignore is still honored. |
Indexing a repo whose .gitignore excludes files you actually want indexed (e.g., generated code committed for cross-repo lookup). |
GITNEXUS_SKIP_OPTIONAL_GRAMMARS |
unset | When =1 strictly, skips vendored grammar materialize/build for tree-sitter-dart, tree-sitter-proto, and tree-sitter-swift at install time. |
Installing on a host without a C++ toolchain or where Swift prebuilds don't match; you're willing to skip Dart/Proto/Swift parsing. |
Publishing to understand-quickly (opt-in)
looptech-ai/understand-quickly is a public registry of code-knowledge graphs that lists gitnexus@1 as a first-class format. After registering your repo once (npx @understand-quickly/cli add or the wizard), gitnexus publish fires a single repository_dispatch event so the registry resyncs your entry on demand instead of waiting for the nightly job.
It is opt-in and a no-op without UNDERSTAND_QUICKLY_TOKEN — a fine-grained GitHub PAT with Repository dispatches: write on the registry repo. Nothing else happens; no graph file is uploaded. See the protocol spec for the full contract.
What Your AI Agent Gets
16 tools exposed via MCP (11 per-repo + 5 group):
| Tool | What It Does | repo Param |
|---|---|---|
list_repos |
Discover all indexed repositories | — |
query |
Process-grouped hybrid search (BM25 + semantic + RRF) | Optional |
context |
360-degree symbol view — categorized refs, process participation | Optional |
impact |
Blast radius analysis with depth grouping and confidence | Optional |
detect_changes |
Git-diff impact — maps changed lines to affected processes | Optional |
rename |
Multi-file coordinated rename with graph + text search | Optional |
cypher |
Raw Cypher graph queries | Optional |
group_list |
List configured repository groups | — |
group_sync |
Extract contracts and match across repos/services | — |
group_contracts |
Inspect extracted contracts and cross-links | — |
group_query |
Search execution flows across all repos in a group | — |
group_status |
Check staleness of repos in a group | — |
When only one repo is indexed, the
repoparameter is optional. With multiple repos, specify which one:query({query: "auth", repo: "my-app"}).
Resources for instant context:
| Resource | Purpose |
|---|---|
gitnexus://repos |
List all indexed repositories (read this first) |
gitnexus://repo/{name}/context |
Codebase stats, staleness check, and available tools |
gitnexus://repo/{name}/clusters |
All functional clusters with cohesion scores |
gitnexus://repo/{name}/cluster/{name} |
Cluster members and details |
gitnexus://repo/{name}/processes |
All execution flows |
gitnexus://repo/{name}/process/{name} |
Full process trace with steps |
gitnexus://repo/{name}/schema |
Graph schema for Cypher queries |
2 MCP prompts for guided workflows:
| Prompt | What It Does |
|---|---|
detect_impact |
Pre-commit change analysis — scope, affected processes, risk level |
generate_map |
Architecture documentation from the knowledge graph with mermaid diagrams |
4 agent skills installed to .claude/skills/ automatically:
- Exploring — Navigate unfamiliar code using the knowledge graph
- Debugging — Trace bugs through call chains
- Impact Analysis — Analyze blast radius before changes
- Refactoring — Plan safe refactors using dependency mapping
Repo-specific skills generated with --skills:
When you run gitnexus analyze --skills, GitNexus detects the functional areas of your codebase (via Leiden community detection) and generates a SKILL.md file for each one under .claude/skills/generated/. Each skill describes a module's key files, entry points, execution flows, and cross-area connections — so your AI agent gets targeted context for the exact area of code you're working in. Skills are regenerated on each --skills run to stay current with the codebase.
Multi-Repo MCP Architecture
GitNexus uses a global registry so one MCP server can serve multiple indexed repos. No per-project MCP config needed — set it up once and it works everywhere.
flowchart TD
subgraph CLI [CLI Commands]
Setup["gitnexus setup"]
Analyze["gitnexus analyze"]
Clean["gitnexus clean"]
List["gitnexus list"]
end
subgraph Registry ["~/.gitnexus/"]
RegFile["registry.json"]
end
subgraph Repos [Project Repos]
RepoA[".gitnexus/ in repo A"]
RepoB[".gitnexus/ in repo B"]
end
subgraph MCP [MCP Server]
Server["server.ts"]
Backend["LocalBackend"]
Pool["Connection Pool"]
ConnA["LadybugDB conn A"]
ConnB["LadybugDB conn B"]
end
Setup -->|"writes global MCP config"| CursorConfig["~/.cursor/mcp.json"]
Analyze -->|"registers repo"| RegFile
Analyze -->|"stores index"| RepoA
Clean -->|"unregisters repo"| RegFile
List -->|"reads"| RegFile
Server -->|"reads registry"| RegFile
Server --> Backend
Backend --> Pool
Pool -->|"lazy open"| ConnA
Pool -->|"lazy open"| ConnB
ConnA -->|"queries"| RepoA
ConnB -->|"queries"| RepoB
How it works: Each gitnexus analyze stores the index in .gitnexus/ inside the repo (portable, gitignored) and registers a pointer in ~/.gitnexus/registry.json. When an AI agent starts, the MCP server reads the registry and can serve any indexed repo. LadybugDB connections are opened lazily on first query and evicted after 5 minutes of inactivity (max 5 concurrent). If only one repo is indexed, the repo parameter is optional on all tools — agents don't need to change anything.
Web UI (browser-based)
A client-side graph explorer and AI chat — your code never leaves your machine.
Try it now: gitnexus.vercel.app — run npx gitnexus@latest serve locally and the page auto-connects to your local backend.
Or run the frontend locally:
git clone https://github.com/abhigyanpatwari/gitnexus.git
cd gitnexus/gitnexus-shared && npm install && npm run build
cd ../gitnexus-web && npm install
npm run dev
# Then in another terminal, start the backend the frontend connects to:
npx gitnexus@latest serve
Docker
The official Docker setup ships two signed images orchestrated by docker-compose.yaml. Each image is published to both GitHub Container Registry (GHCR) and Docker Hub — same build, same digest, same Cosign signature — so pick whichever registry you prefer:
| Purpose | GHCR (default in docker-compose.yaml) |
Docker Hub mirror |
|---|---|---|
CLI / gitnexus serve backend (HTTP API on port 4747, MCP, indexer) |
ghcr.io/abhigyanpatwari/gitnexus:latest |
akonlabs/gitnexus:latest |
Static web UI (port 4173) |
ghcr.io/abhigyanpatwari/gitnexus-web:latest |
akonlabs/gitnexus-web:latest |
Heads-up — image rename. Earlier releases published the web UI under
ghcr.io/abhigyanpatwari/gitnexus. Starting with the introduction of the bundled backend, that slug now hosts the CLI/server image and the UI moved toghcr.io/abhigyanpatwari/gitnexus-web. The previous tags remain available for pulling, but new versions are only published under the new slugs. Update yourdocker run/ compose files accordingly (or just adopt the bundled compose).
One-command setup
docker compose up -d
This starts the server on http://localhost:4747 and the web UI on
http://localhost:4173. The UI auto-detects the server because the browser
runs on the host and reaches the container via the mapped port.
A named volume (gitnexus-data) persists the global registry, indexes, and
cloned repos at /data/gitnexus inside the server container. To make repos on
your host machine indexable, set WORKSPACE_DIR before bringing the stack up:
WORKSPACE_DIR=$HOME/code docker compose up -d
# Inside the server container the directory is mounted read-only at /workspace.
docker compose exec gitnexus-server gitnexus index /workspace/my-repo
Direct docker run
# Server
docker run --rm -d \
--name gitnexus-server \
-p 4747:4747 \
-v gitnexus-data:/data/gitnexus \
ghcr.io/abhigyanpatwari/gitnexus:latest
# Web UI
docker run --rm -d \
--name gitnexus-web \
-p 4173:4173 \
ghcr.io/abhigyanpatwari/gitnexus-web:latest
Optional env file (override image tags, container names, ports, workspace dir):
cp .env.example .env
docker compose --env-file .env up -d
Versioning & supply-chain protection
The Docker images are version-locked to the npm package:
- Stable images are only published from
vX.Y.Zgit tags (viadocker.ymltriggered directly by the tag push), and the workflow refuses to build unless the tag exactly matchesgitnexus/package.json's version. Soghcr.io/abhigyanpatwari/gitnexus:1.6.2(and its Docker Hub mirrorakonlabs/gitnexus:1.6.2) is byte-for-byte the same release asnpm install gitnexus@1.6.2— no drift, no floating builds frommain. Both registries receive the same digest from a single build step, so you can pull from either and the signature verifies identically. - Release-candidate images (e.g.
:1.7.0-rc.1) are published alongside each RC npm release. They are built bypublish.ymlcallingdocker.ymlas a reusable workflow after the RC tag is created and pushed. :latestis auto-promoted only from non-prerelease tags by the Docker metadata action, so it always points at a real, npm-published version.
Both images are signed with Cosign keyless signing using the
workflow's GitHub OIDC identity, and shipped with build provenance and SBOM
attestations. This is your protection against supply-chain attacks: even if
an attacker republishes a same-named image elsewhere (or somehow pushes to a
typo-squatted registry), they cannot forge a Cosign signature tied to
abhigyanpatwari/GitNexus's docker.yml. Always verify before pulling into
sensitive environments:
Stable releases — signed from the v* tag ref:
cosign verify ghcr.io/abhigyanpatwari/gitnexus:1.6.2 \
--certificate-identity-regexp '^https://github\.com/abhigyanpatwari/GitNexus/\.github/workflows/docker\.yml@refs/tags/v[0-9]+\.[0-9]+\.[0-9]+(-[a-zA-Z0-9.]+)?$' \
--certificate-oidc-issuer https://token.actions.githubusercontent.com
# Same signature verifies the Docker Hub mirror (identical digest):
cosign verify docker.io/akonlabs/gitnexus:1.6.2 \
--certificate-identity-regexp '^https://github\.com/abhigyanpatwari/GitNexus/\.github/workflows/docker\.yml@refs/tags/v[0-9]+\.[0-9]+\.[0-9]+(-[a-zA-Z0-9.]+)?$' \
--certificate-oidc-issuer https://token.actions.githubusercontent.com
The regex pins the certificate identity to this repo's docker.yml workflow
run from a v* tag — rejecting unsigned images, images signed by other
workflows, and images signed from unprotected refs. It is identical for both
registries because both sets of tags were signed at the same digest in one
workflow run.
Release candidates — signed from refs/heads/main (the caller's ref when
publish.yml invokes docker.yml as a reusable workflow):
cosign verify ghcr.io/abhigyanpatwari/gitnexus:1.7.0-rc.1 \
--certificate-identity 'https://github.com/abhigyanpatwari/GitNexus/.github/workflows/docker.yml@refs/heads/main' \
--certificate-oidc-issuer https://token.actions.githubusercontent.com
You can also inspect the build provenance and SBOM:
cosign download attestation ghcr.io/abhigyanpatwari/gitnexus:1.6.2 \
--predicate-type https://slsa.dev/provenance/v1
Kubernetes: enforce signatures at admission
For Kubernetes deployments, ship the bundled
ClusterImagePolicy so the
Sigstore policy-controller rejects any GitNexus pod whose
image is not signed by this repo's docker.yml running from a vX.Y.Z tag —
the same identity the cosign verify snippet above pins.
# 1. Install the controller (one-time, cluster-wide)
helm repo add sigstore https://sigstore.github.io/helm-charts && helm repo update
helm install policy-controller -n cosign-system --create-namespace \
sigstore/policy-controller
# 2. Opt your namespace in
kubectl label namespace <your-ns> policy.sigstore.dev/include=true
# 3. Apply the policy
kubectl apply -f deploy/kubernetes/cluster-image-policy.yaml
After this, attempting to deploy an unsigned image — or one signed by anything
other than abhigyanpatwari/GitNexus's docker.yml at a v* tag — fails the
admission webhook before a pod is ever created. This turns the verifiable
signature into an enforced policy, which is the supply-chain control most
clusters actually need.
Files
- Dockerfile.web — builds
gitnexus-sharedandgitnexus-web, then serves the production frontend. - Dockerfile.cli — builds the CLI/server (with its native deps) and runs
gitnexus serve --host 0.0.0.0. - docker-compose.yaml — starts both signed images side by side.
- .env.example — overrides for image names, container names, ports, and the workspace mount.
The web UI uses the same indexing pipeline as the CLI but runs entirely in WebAssembly (Tree-sitter WASM, LadybugDB WASM, in-browser embeddings). It's great for quick exploration but limited by browser memory for larger repos.
Local Backend Mode: Run gitnexus serve and open the web UI locally — it auto-detects the server and shows all your indexed repos, with full AI chat support. No need to re-upload or re-index. The agent's tools (Cypher queries, search, code navigation) route through the backend HTTP API automatically.
The Problem GitNexus Solves
Tools like Cursor, Claude Code, Codex, Cline, Roo Code, and Windsurf are powerful — but they don't truly know your codebase structure.
What happens:
- AI edits
UserService.validate() - Doesn't know 47 functions depend on its return type
- Breaking changes ship
Traditional Graph RAG vs GitNexus
Traditional approaches give the LLM raw graph edges and hope it explores enough. GitNexus precomputes structure at index time — clustering, tracing, scoring — so tools return complete context in one call:
flowchart TB
subgraph Traditional["Traditional Graph RAG"]
direction TB
U1["User: What depends on UserService?"]
U1 --> LLM1["LLM receives raw graph"]
LLM1 --> Q1["Query 1: Find callers"]
Q1 --> Q2["Query 2: What files?"]
Q2 --> Q3["Query 3: Filter tests?"]
Q3 --> Q4["Query 4: High-risk?"]
Q4 --> OUT1["Answer after 4+ queries"]
end
subgraph GN["GitNexus Smart Tools"]
direction TB
U2["User: What depends on UserService?"]
U2 --> TOOL["impact UserService upstream"]
TOOL --> PRECOMP["Pre-structured response:
8 callers, 3 clusters, all 90%+ confidence"]
PRECOMP --> OUT2["Complete answer, 1 query"]
end
Core innovation: Precomputed Relational Intelligence
- Reliability — LLM can't miss context, it's already in the tool response
- Token efficiency — No 10-query chains to understand one function
- Model democratization — Smaller LLMs work because tools do the heavy lifting
How It Works
GitNexus builds a complete knowledge graph of your codebase through a multi-phase indexing pipeline:
- Structure — Walks the file tree and maps folder/file relationships
- Parsing — Extracts functions, classes, methods, and interfaces using Tree-sitter ASTs
- Resolution — Resolves imports, function calls, heritage, constructor inference, and
self/thisreceiver types across files with language-aware logic - Clustering — Groups related symbols into functional communities
- Processes — Traces execution flows from entry points through call chains
- Search — Builds hybrid search indexes for fast retrieval
Supported Languages
| Language | Imports | Named Bindings | Exports | Heritage | Type Annotations | Constructor Inference | Config | Frameworks | Entry Points |
|---|---|---|---|---|---|---|---|---|---|
| TypeScript | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| JavaScript | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ | ✓ | ✓ |
| Python | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Java | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ |
| Kotlin | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ |
| C# | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Go | ✓ | — | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Rust | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ |
| PHP | ✓ | ✓ | ✓ | — | ✓ | ✓ | ✓ | ✓ | ✓ |
| Ruby | ✓ | — | ✓ | ✓ | — | ✓ | — | ✓ | ✓ |
| Swift | — | — | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| C | — | — | ✓ | — | ✓ | ✓ | — | ✓ | ✓ |
| C++ | — | — | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ |
| Dart | ✓ | — | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ |
Imports — cross-file import resolution · Named Bindings — import { X as Y } / re-export tracking · Exports — public/exported symbol detection · Heritage — class inheritance, interfaces, mixins · Type Annotations — explicit type extraction for receiver resolution · Constructor Inference — infer receiver type from constructor calls (self/this resolution included for all languages) · Config — language toolchain config parsing (tsconfig, go.mod, etc.) · Frameworks — AST-based framework pattern detection · Entry Points — entry point scoring heuristics
Tool Examples
Impact Analysis
impact({target: "UserService", direction: "upstream", minConfidence: 0.8})
TARGET: Class UserService (src/services/user.ts)
UPSTREAM (what depends on this):
Depth 1 (WILL BREAK):
handleLogin [CALLS 90%] -> src/api/auth.ts:45
handleRegister [CALLS 90%] -> src/api/auth.ts:78
UserController [CALLS 85%] -> src/controllers/user.ts:12
Depth 2 (LIKELY AFFECTED):
authRouter [IMPORTS] -> src/routes/auth.ts
Options: maxDepth, minConfidence, relationTypes (CALLS, IMPORTS, EXTENDS, IMPLEMENTS), includeTests, limit (max symbols per depth, default 100), offset (pagination start per depth), summaryOnly (counts and risk only, omits symbol list)
Disambiguation — when several symbols share the target name, impact returns a ranked ambiguous candidate list instead of guessing. Narrow it with target_uid (exact, zero-ambiguity), file_path, or kind (Function, Class, Method, …). From the CLI these are --uid, --file, and --kind, matching gitnexus context:
gitnexus impact get_embeddings # → ambiguous: lists ranked candidates
gitnexus impact get_embeddings --file src/embed.py # → resolves to the one in that file
gitnexus impact get_embeddings --uid "Function:src/embed.py:get_embeddings" # exact
Process-Grouped Search
query({query: "authentication middleware"})
processes:
- summary: "LoginFlow"
priority: 0.042
symbol_count: 4
process_type: cross_community
step_count: 7
process_symbols:
- name: validateUser
type: Function
filePath: src/auth/validate.ts
process_id: proc_login
step_index: 2
definitions:
- name: AuthConfig
type: Interface
filePath: src/types/auth.ts
Context (360-degree Symbol View)
context({name: "validateUser"})
symbol:
uid: "Function:validateUser"
kind: Function
filePath: src/auth/validate.ts
startLine: 15
incoming:
calls: [handleLogin, handleRegister, UserController]
imports: [authRouter]
outgoing:
calls: [checkPassword, createSession]
processes:
- name: LoginFlow (step 2/7)
- name: RegistrationFlow (step 3/5)
Detect Changes (Pre-Commit)
detect_changes({scope: "all"})
summary:
changed_count: 12
affected_count: 3
changed_files: 4
risk_level: medium
changed_symbols: [validateUser, AuthService, ...]
affected_processes: [LoginFlow, RegistrationFlow, ...]
Rename (Multi-File)
rename({symbol_name: "validateUser", new_name: "verifyUser", dry_run: true})
status: success
files_affected: 5
total_edits: 8
graph_edits: 6 (high confidence)
text_search_edits: 2 (review carefully)
changes: [...]
Cypher Queries
-- Find what calls auth functions with high confidence
MATCH (c:Community {heuristicLabel: 'Authentication'})<-[:CodeRelation {type: 'MEMBER_OF'}]-(fn)
MATCH (caller)-[r:CodeRelation {type: 'CALLS'}]->(fn)
WHERE r.confidence > 0.8
RETURN caller.name, fn.name, r.confidence
ORDER BY r.confidence DESC
Wiki Generation
Generate LLM-powered documentation from your knowledge graph:
# Requires an LLM API key (OPENAI_API_KEY, etc.)
gitnexus wiki
# Use a custom model or provider
gitnexus wiki --model gpt-4o
gitnexus wiki --base-url https://api.anthropic.com/v1
# Force full regeneration
gitnexus wiki --force
# Increase the timeout or retries for large codebase or slow LLM providers
gitnexus wiki --timeout <seconds> # LLM request timeout in seconds (default: disabled)
gitnexus wiki --retries <n> # Max LLM retry attempts per request (default: 3)
# Change the language generation for wiki
gitnexus wiki --lang <lang> # Output language for generated documentation (e.g. english, chinese, spanish, japanese)
The wiki generator reads the indexed graph structure, groups files into modules via LLM, generates per-module documentation pages, and creates an overview page — all with cross-references to the knowledge graph.
Tech Stack
| Layer | CLI | Web |
|---|---|---|
| Runtime | Node.js (native) | Browser (WASM) |
| Parsing | Tree-sitter native bindings | Tree-sitter WASM |
| Database | LadybugDB native | LadybugDB WASM |
| Embeddings | HuggingFace transformers.js (GPU/CPU) | transformers.js (WebGPU/WASM) |
| Search | BM25 + semantic + RRF | BM25 + semantic + RRF |
| Agent Interface | MCP (stdio) | LangChain ReAct agent |
| Visualization | — | Sigma.js + Graphology (WebGL) |
| Frontend | — | React 18, TypeScript, Vite, Tailwind v4 |
| Clustering | Graphology | Graphology |
| Concurrency | Worker threads + async | Web Workers + Comlink |
Roadmap
Actively Building
- LLM Cluster Enrichment — Semantic cluster names via LLM API
- AST Decorator Detection — Parse @Controller, @Get, etc.
- Incremental Indexing — Only re-index changed files
Recently Completed
- Constructor-Inferred Type Resolution,
self/thisReceiver Mapping - Wiki Generation, Multi-File Rename, Git-Diff Impact Analysis
- Process-Grouped Search, 360-Degree Context, Claude Code Hooks
- Multi-Repo MCP, Zero-Config Setup, 14 Language Support
- Community Detection, Process Detection, Confidence Scoring
- Hybrid Search, Vector Index
Security & Privacy
- CLI: Everything runs locally on your machine. No network calls. Index stored in
.gitnexus/(gitignored). Global registry at~/.gitnexus/stores only paths and metadata. - Web: Everything runs in your browser. No code uploaded to any server. API keys stored in localStorage only.
- Open source — audit the code yourself.
Acknowledgments
- Tree-sitter — AST parsing
- LadybugDB — Embedded graph database with vector support (formerly KuzuDB)
- Sigma.js — WebGL graph rendering
- transformers.js — Browser ML
- Graphology — Graph data structures
- MCP — Model Context Protocol