flowchart LR
    R["Shared tool registry<br/>(finagent.tools)"] --- Agent["Agent loop<br/>Claude / OpenAI"]
    R --- MCP["MCP server<br/>(FastMCP)"]
    U[User] --> Agent --> Ans[Answer + tool trace]
    Host["MCP client<br/>(Claude Desktop)"] --> MCP

# Install (Python 3.10+)
pip install -e .
pip install -r requirements.txt

# Configure
cp .env.example .env       # add ANTHROPIC_API_KEY (or set LLM_PROVIDER=openai)

# Ask the agent (it will call tools and show its work)
python scripts/chat.py "If I save $300/month at 8% for 25 years, how much will I have?"
python scripts/chat.py "Monthly payment on a $250k mortgage at 6.5% over 30 years?"
python scripts/chat.py "Convert 5000 BRL to USD, then grow it at 10% for 5 years."

=== Tool calls ===
  • future_value_of_savings({'monthly_contribution': 300, 'annual_rate_pct': 8, 'years': 25}) -> {'future_value': 285809.08, ...}
=== Answer ===
Saving $300/month at 8% for 25 years grows to about $285,809.

python -m finagent.mcp_server

{
  "mcpServers": {
    "finance-agent": {
      "command": "python",
      "args": ["-m", "finagent.mcp_server"]
    }
  }
}

finance-agent-mcp/
├── src/finagent/
│   ├── tools.py        # the shared tool registry (pure functions + schemas)
│   ├── agent.py        # provider-swappable tool-use loop
│   ├── mcp_server.py   # exposes the registry over MCP (FastMCP)
│   └── config.py
├── scripts/chat.py     # CLI agent
├── tests/test_tools.py # pure unit tests (no key)
└── docs/architecture.md

pytest -q     # tests the finance math directly — no API key required