aegis-finance-mcp

# aegis-finance-mcp **Aegis** is an autonomous personal-finance analyst & guardian, exposed as an [MCP](https://modelcontextprotocol.io) server. It categorizes your transactions, finds money leaks (duplicate charges, subscription hikes), summarizes spending, and reports account balances/due dates — and it answers **only** from tools, so figures trace back to your real data instead of being hallucinated. This package ships the MCP server so any MCP host (Cursor, Claude Desktop, or your own agent) can call Aegis's finance tools locally. ## Install & run ```bash # One-shot, no install needed: uvx aegis-finance-mcp # or install it: pip install aegis-finance-mcp aegis-finance-mcp # starts the MCP server over stdio ``` ## Use it from an MCP host Add it to your host's MCP config (example shape): ```json { "mcpServers": { "aegis": { "command": "uvx", "args": ["aegis-finance-mcp"] } } } ``` Then ask things like *"Should I pay my statement now, or dispute anything first?"* — the host will call the exposed tools: `list_accounts`, `spending_summary`, `scan_for_leaks`, and `get_transactions`. ## Configuration (environment variables) | Variable | Purpose | |----------|---------| | `OPENAI_API_KEY` | LLM-quality categorization & summaries (falls back to rule-based if unset) | | `SOPHTRON_USER_ID`, `SOPHTRON_ACCESS_KEY` | Live account aggregation; **without these, Aegis runs on a bundled synthetic sample** so you can try it safely | No aggregator credentials are required to evaluate the server — it works out of the box on sample data. ## Learn more Full architecture, evaluation/observability stack, CrewAI crew, RAG chat, and the feedback loop are documented in the project repository: <https://github.com/parul6695/paruls-ai-agents/tree/main/7_aegis> MIT licensed.