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docs: add finance+compliance demo table and client code snippet

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Ishaan Jaffer 2026-03-21 17:39:53 -07:00
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docs/my-website/docs/mcp_chat_completions_orchestration.md
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@ -183,6 +183,80 @@ curl -X POST http://localhost:4000/v1/agents \
The proxy wraps each registered agent as a function tool. When the LLM calls it, the proxy sends a JSON-RPC `message/send` to the agent and returns the result as a tool message.
## Real-world example — Finance MCP + Compliance Agent
Register a finance calculation MCP server and a compliance analyst A2A agent once. Every request can then use both without knowing any server URLs.
```python
import openai
client = openai.OpenAI(
api_key="sk-1234",
base_url="http://localhost:4000",
)
# MCP only — financial calculation
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{
"role": "user",
"content": "What is the monthly repayment on a £250,000 mortgage at 4.5% APR over 25 years?"
}],
tools=[{
"type": "mcp",
"server_url": "litellm_proxy/mcp",
"require_approval": "never",
}],
)
# → calls calculate_loan_payment tool → £1,389.58/mo
# Both MCP + Agent in a single call
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{
"role": "user",
"content": (
"Calculate compound interest on £100,000 at 2.8% over 3 years, "
"then draft a compliance note summarising the outcome for the audit file."
)
}],
tools=[
{
"type": "mcp",
"server_url": "litellm_proxy/mcp",
"require_approval": "never",
},
{
"type": "a2a_agent",
"server_url": "litellm_proxy/agents",
"require_approval": "never",
},
],
)
# → calls calculate_compound_interest (£8,637.40 interest) AND compliance_analyst agent
# → final answer includes both the numbers and the audit-ready compliance note
```
### Demo results (10 scenarios, local proxy, gpt-4o-mini)
MCP server registered: `finance` — `calculate_compound_interest`, `convert_currency`, `calculate_loan_payment`, `calculate_var`
Agent registered: `compliance_analyst` — Basel III, KYC, VaR, earnings, trade summaries
| # | Scenario | MCP | Agent | Tool Called | Result |
|---|----------|:---:|:---:|-------------|--------|
| 1 | Mortgage repayment | ✓ | — | `calculate_loan_payment(£250k, 4.5%, 25yr)` | **£1,389.58/mo** |
| 2 | FX conversion GBP→USD | ✓ | — | `convert_currency(£1.25M, 1.2738)` | £1,592,250 USD |
| 3 | Compound interest | ✓ | — | `calculate_compound_interest(£50k, 3.5%, 5yr)` | **£9,384 interest** |
| 4 | Basel III notice | — | ✓ | `compliance_analyst` | CET1 ≥4.5%, Tier1 ≥6% — review capital position |
| 5 | KYC note | — | ✓ | `compliance_analyst` | Entity verified, no sanctions, onboarding approved |
| 6 | VaR calculation | ✓ | ✓ | `calculate_var(£5M, 0.8% vol, 99%)` | 1-day VaR **£93,040**, 10-day **£294,218** |
| 7 | Interest calc + audit note | ✓ | ✓ | `calculate_compound_interest` + `compliance_analyst` | **£8,637 interest** + audit-ready compliance note |
| 8 | Mortgage refinance | ✓ | ✓ | `calculate_loan_payment(£180k, 3.9%, 20yr)` | **£1,081.30/mo** |
| 9 | Large FX GBP→JPY | ✓ | — | `convert_currency(£2.5M, 191.45)` | **¥478,625,000** |
| 10 | Earnings summary | — | ✓ | `compliance_analyst` | NII +8% YoY, CET1=13.8%, guidance reaffirmed |
Row 7 demonstrates the orchestrator routing a single request to **both** the MCP finance server and the compliance analyst agent — the LLM received the calculation result from MCP and the formatted audit note from the agent in one turn, with no URL configuration in the client.
## Semantic filter
Add `"semantic_filter": true` to only inject tools relevant to the user's query. Useful when you have many registered servers and want to keep the LLM context lean.