fca-mcp

trailblazelabs/fca-mcp

3.1

If you are the rightful owner of fca-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to dayong@mcphub.com.

The FCA MCP Server is an open-source AI-powered regulatory intelligence tool designed to streamline access to financial regulatory data.

Tools
8
Resources
0
Prompts
0

FCA MCP Server

Open-source AI-powered regulatory intelligence for financial services

MIT License Python 3.12+

🎯 What This Solves

Financial services firms waste hours every day manually searching through fragmented FCA databases for regulatory information. Our open-source FCA MCP Server transforms this experience by providing real-time, conversational access to live FCA Register data through AI interfaces.

Instead of this: Manual searches across multiple FCA portals, copying firm reference numbers, cross-referencing databases You get this: "Which firms can provide mortgage advice in Scotland?" → Instant, accurate answers with source citations

🚀 Key Benefits

  • 70% reduction in regulatory research time
  • Real-time data from live FCA APIs (not static databases)
  • Open source - inspect, modify, and extend freely
  • Conversational interface - ask questions in plain English
  • Zero licensing costs - available to all financial services firms

🎬 Demo

See the FCA MCP Server in action:

Watch a 2-minute demo showing how regulatory questions that normally take hours are answered in seconds

https://github.com/user-attachments/assets/54d5e08c-ca84-4e9a-95c4-4251ca5af51e

Demo Scenarios:

  • 🏛️ Digital Asset Startup: "Do I need FCA authorization for my custody solution?"
  • 💼 Investment Advisory: "What are current suitability rules for high-net-worth clients?"
  • 📊 Market Intelligence: "Find all authorized wealth management firms in London"

How It Works

Our MCP (Model Context Protocol) server acts as a bridge between AI assistants like Claude Desktop and the FCA's regulatory data. It:

  1. Continuously ingests data from all FCA Register endpoints
  2. Processes and normalises the information for AI consumption
  3. Exposes conversational tools for natural language queries
  4. Returns real-time results with proper citations and context

Architecture: FastMCP server → Elasticsearch with semantic search → Azure OpenAI embeddings → Live FCA APIs

🛠️ Available Tools

The MCP Server provides these AI-accessible tools:

  • search_fca_handbook - Search FCA Handbook rules and guidance
  • search_policy_statements - Find FCA Policy Statements by content
  • search_consultation_papers - Search regulatory proposals and consultations
  • search_authorised_firms - Query the FCA register of authorised firms
  • search_enforcement_notices - Search enforcement actions and fines
  • get_firm_details - Get comprehensive firm information
  • search_guidance_documents - Find FCA guidance and technical standards
  • get_regulatory_updates - Get latest regulatory announcements

🎯 Use Cases

For Compliance Teams:

  • "Find all firms with mortgage advice permissions in my region"
  • "What enforcement actions were taken for conduct breaches this year?"
  • "Show me recent policy changes affecting investment firms"

For Legal & Risk:

  • "Search FCA Handbook for rules about operational resilience"
  • "Find consultation papers on crypto asset regulations"
  • "What are the current requirements for ESG reporting?"

For Business Development:

  • "Which competitors have similar FCA permissions to us?"
  • "Find recently authorised fintech firms"
  • "Show me regulatory barriers for new product launches"

🚀 Quick Start (5 Minutes)

Prerequisites: Docker, Node.js, Claude Desktop, Azure OpenAI API key

  1. Clone and configure:

    git clone https://github.com/trailblazelabs/fca-mcp.git
cd fca-mcp
cp .env.example .env
# Edit .env with your Azure OpenAI credentials

  2. One-command setup:

    make dev_setup_from_scratch

  3. Connect to Claude Desktop:

    {
  "mcpServers": {
    "fca-mcp": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:8080/mcp/", "--allow-http"]
    }
  }
}

  4. Start asking questions!

    • "Search for wealth management firms in London"
    • "Find recent enforcement notices about market manipulation"
    • "Show me policy changes affecting crypto firms"

🔧 Technical Deep Dive

Prerequisites for Local Development

  • Python >= 3.12
  • uv (Python package manager)
  • Docker and Docker Compose
  • Node.js (for mcp-remote)

Local Development Setup

  1. Install uv (if not already installed):

    curl -LsSf https://astral.sh/uv/install.sh | sh

  2. Clone and set up the project:

    git clone <repository>
cd fca-mcp

# Install dependencies with uv
uv sync --extra dev

  3. Available Make commands:

    make install           # Install all dependencies
make test              # Run tests
make test_integration  # Run integration tests (slow on first run)
make lint              # Check code formatting
make format            # Format and fix code
make safe              # Run security checks

# Pre-commit hooks
make pre-commit-install  # Install pre-commit hooks
make pre-commit         # Run pre-commit on all files

# Docker operations
make run             # Start services with Docker Compose
make stop            # Stop Docker services
make logs            # View MCP server logs

# Development helpers
make mcp_test        # Test MCP server connection
make es_health       # Check Elasticsearch health

  4. Run the MCP server locally:

    make run_mcp_server
# Or directly with uv:
uv run fca-mcp serve

Project Structure

fca-mcp/
├── fca_mcp/                 # Main Python package
│   ├── cli.py               # CLI interface
│   ├── models.py            # Data models
│   ├── mcp_server/          # MCP server implementation
│   │   ├── api.py           # API endpoints and tool definitions
│   │   ├── handlers.py      # Elasticsearch query handlers
│   │   ├── main.py          # FastAPI application setup
│   │   └── utils.py         # Utility functions
│   └── ...                  # Other modules
├── tests/                   # Test suite
│   ├── mcp_server/          # MCP server tests
│   └── ...                  # Other tests
├── Dockerfile.mcp-server    # MCP server container configuration
├── docker-compose.yaml      # Service orchestration
└── README.md                # This file

CLI Commands

The project includes a unified CLI for data management and server operations:

# Initialize Elasticsearch indices and inference endpoints
fca-mcp init-elasticsearch

# Run the MCP server
fca-mcp serve

# Load different types of FCA data
fca-mcp load-data handbook
fca-mcp load-data policy-documents
fca-mcp load-data consultation-papers
fca-mcp load-data firms-register
fca-mcp load-data enforcement-notices

# Delete all data
fca-mcp delete-elasticsearch

Data Structure

The system works with several types of FCA regulatory documents:

FCA Handbook (Index: fca_mcp_handbook):

  • Rules and guidance sections with semantic search
  • Cross-references between sections
  • Section hierarchy and numbering

Policy Statements (Index: fca_mcp_policy_statements):

  • Final policy decisions and statements
  • Semantic search on policy content
  • PS number references and dates

Consultation Papers (Index: fca_mcp_consultation_papers):

  • Regulatory proposals and consultations
  • Comment periods and responses
  • CP number references

Authorised Firms (Index: fca_mcp_authorised_firms):

  • Firms and individuals register
  • Permissions and restrictions
  • Contact and status information

Enforcement Notices (Index: fca_mcp_enforcement_notices):

  • Disciplinary actions and fines
  • Decision notices and final notices
  • Firm and individual sanctions

Data Loading Process:

  1. Fetch from FCA APIs and web sources
  2. Transform into structured models with computed fields
  3. Embed using Azure OpenAI for semantic search
  4. Index into Elasticsearch with proper mappings

Daily Data Ingestion

To keep the FCA data up-to-date, a daily ingestion mechanism is provided:

make ingest_daily

This runs the equivalent of:

fca-mcp load-data handbook --incremental
fca-mcp load-data policy-documents --recent
fca-mcp load-data enforcement-notices --recent

Usage Examples

Once connected to Claude, you can use natural language queries like:

FCA Handbook:

  • "Search the FCA Handbook for rules about mortgage lending"
  • "Find guidance on consumer credit regulations"
  • "Show me the latest updates to conduct of business rules"

Policy and Consultation:

  • "Find policy statements about ESG and sustainability"
  • "Search consultation papers on crypto asset regulations"
  • "Show me recent policy changes affecting investment firms"

Firm Information:

  • "Search for authorised wealth management firms in London"
  • "Find details about a specific firm's permissions"
  • "Show me recent authorisation decisions"

Enforcement:

  • "Search enforcement notices about market manipulation"
  • "Find recent fines for conduct breaches"
  • "Show me disciplinary actions against individuals"

Regulatory Research:

  • "Find all FCA guidance on operational resilience"
  • "Search for rules affecting fintech companies"
  • "Show me consumer protection requirements for investments"

Logs and Debugging

View server logs:

docker-compose logs mcp-server

Enable debug mode in Claude config by adding --debug flag.

Check Elasticsearch status:

curl http://localhost:9200/_cat/health?v
# Or use the make command:
make es_health

Troubleshooting

Common Issues

MCP Connection Issues

  • Ensure MCP server is running on port 8080
  • The MCP server runs on /{MCP_ROOT_PATH}/mcp, not /MCP_ROOT_PATH
  • Verify Claude Desktop configuration is correct

Data Loading Failures

  • Check Azure OpenAI credentials in .env file
  • Ensure Elasticsearch is running and accessible
  • Verify network connectivity to FCA APIs and websites
  • Use --ll DEBUG flag for detailed logging

Elasticsearch issues

  • Verify inference endpoints are created: fca-mcp init-elasticsearch
  • Use https://elasticvue.com/ to inspect the Elasticsearch instance

Optional: Parliamentary horizon scanning (Enterprise)

Forward‑looking risk monitoring to anticipate regulatory change:

  • HM Treasury and Select Committee hearings (Hansard)
  • Financial Services Acts and Statutory Instruments affecting FCA perimeter
  • Treasury consultations and policy statements

This module is available in the Enterprise edition and integrates with the same MCP interface for proactive alerts and research.

Contact

Interested in enterprise access or collaboration?

📅 Schedule a call: https://cal.com/trailblazelabs

License

MIT License - see LICENSE file for details