Financial Intelligence Server
FreeNot checkedA production-grade MCP server that provides financial ML tools including RAG search, anomaly detection, contract summarization, vendor graph analysis, and model
About
A production-grade MCP server that provides financial ML tools including RAG search, anomaly detection, contract summarization, vendor graph analysis, and model drift monitoring using entirely free, open-source components.
README
A production-grade Model Context Protocol (MCP) server that exposes financial ML tools to any MCP-compatible AI client (Claude Desktop, Cursor, etc.).
Built entirely with free, open-source tools — no paid APIs required.
🏗️ Architecture
┌─────────────────────────────────────────────────────────────────┐
│ MCP-Compatible Client │
│ (Claude Desktop / Cursor / Any LLM) │
└─────────────────────┬───────────────────────────────────────────┘
│ MCP Protocol (stdio)
▼
┌─────────────────────────────────────────────────────────────────┐
│ financial-mcp-server │
│ server.py │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Tool Router │ │
│ └──┬────────────┬────────────┬───────────┬─────────────────┘ │
│ │ │ │ │ │ │
│ ▼ ▼ ▼ ▼ ▼ │
│ ┌───────┐ ┌─────────┐ ┌────────┐ ┌────────┐ ┌─────────┐ │
│ │ RAG │ │Anomaly │ │Contract│ │Vendor │ │ Drift │ │
│ │Search │ │Detect. │ │Summary │ │ Graph │ │Monitor │ │
│ └───┬───┘ └────┬────┘ └───┬────┘ └───┬────┘ └────┬────┘ │
└─────┼───────────┼───────────┼───────────┼────────────┼─────────┘
│ │ │ │ │
▼ ▼ ▼ ▼ ▼
FAISS + sklearn Ollama Neo4j / Evidently
sentence- IsolationF. (local LLM) NetworkX AI / KS
transformers (free) (free) (free) Test (free)
🛠️ Tools
| Tool | Description | Free Stack Used |
|---|---|---|
search_financial_docs |
RAG over financial PDFs/docs | FAISS + sentence-transformers + Ollama |
analyze_expense_pattern |
Anomaly detection on transactions | scikit-learn IsolationForest |
summarize_contract |
Extract key clauses from contracts | Ollama Mistral + regex fallback |
get_vendor_relationships |
Query vendor knowledge graph | Neo4j Community + NetworkX fallback |
monitor_model_drift |
Detect data/feature drift in models | Evidently AI + scipy KS test fallback |
💸 100% Free Stack
| Component | Tool | Cost |
|---|---|---|
| LLM | Ollama + Mistral 7B (local) | FREE |
| Embeddings | sentence-transformers all-MiniLM-L6-v2 | FREE |
| Vector Store | FAISS (Meta) | FREE |
| Anomaly Detection | scikit-learn IsolationForest | FREE |
| Graph Database | Neo4j Community Edition | FREE |
| Drift Monitoring | Evidently AI open-source | FREE |
| MCP Framework | Anthropic MCP Python SDK | FREE |
🚀 Quick Start
1. Clone & Install
git clone https://github.com/YOUR_USERNAME/financial-mcp-server.git
cd financial-mcp-server
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
2. Start Ollama (free local LLM)
# Install Ollama from https://ollama.com (free)
ollama serve
ollama pull mistral # ~4GB download, one time
3. Add Your Documents (optional)
# Drop any .txt, .md, or .pdf files into:
data/sample_docs/
# Index them (auto-happens on first run, or manually):
python -c "from tools.rag_search import _load_or_build_index; _load_or_build_index()"
4. Run the MCP Server
python server.py
5. Connect to Claude Desktop
Edit your Claude Desktop config file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"financial-intelligence": {
"command": "python",
"args": ["/absolute/path/to/financial-mcp-server/server.py"],
"env": {
"PYTHONPATH": "/absolute/path/to/financial-mcp-server"
}
}
}
}
Restart Claude Desktop. You'll see the 🔧 tools icon appear.
🐳 Docker Setup (with Neo4j)
# Start Neo4j Community Edition + MCP server
docker-compose up -d
# Check logs
docker-compose logs -f mcp-server
Neo4j browser available at: http://localhost:7474
🧪 Run Tests
pip install pytest
pytest tests/ -v
💬 Example Claude Desktop Conversations
Once connected, ask Claude:
"Search my financial documents for information about payment terms with TechVendor Solutions"
"Analyze these transactions for anomalies: [paste JSON list]"
"Summarize this contract and flag any risky clauses: [paste contract text]"
"What vendors are related to TechVendor Solutions and what's their risk level?"
"Check if the fraud_detector model has drifted and whether it needs retraining"
📁 Project Structure
financial-mcp-server/
├── server.py # MCP server — tool registry & routing
├── tools/
│ ├── rag_search.py # search_financial_docs
│ ├── anomaly_detection.py # analyze_expense_pattern
│ ├── contract_summary.py # summarize_contract
│ ├── vendor_graph.py # get_vendor_relationships
│ └── drift_monitor.py # monitor_model_drift
├── data/
│ └── sample_docs/ # Drop your financial docs here
├── tests/
│ └── test_tools.py # pytest test suite
├── .github/workflows/
│ └── ci.yml # GitHub Actions CI
├── Dockerfile
├── docker-compose.yml # Includes Neo4j Community Edition
├── requirements.txt
└── claude_desktop_config.json # Copy into Claude Desktop config
🔗 Related Projects
- Financial-RAG-Pipeline — Standalone RAG system (precursor to this project)
📄 License
MIT License — free to use, modify, and distribute.
Installing Financial Intelligence Server
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/BharathiDonku7/MCP-ServerFAQ
Is Financial Intelligence Server MCP free?
Yes, Financial Intelligence Server MCP is free — one-click install via Unyly at no cost.
Does Financial Intelligence Server need an API key?
No, Financial Intelligence Server runs without API keys or environment variables.
Is Financial Intelligence Server hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Financial Intelligence Server in Claude Desktop, Claude Code or Cursor?
Open Financial Intelligence Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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