Boston Core MCP

Safe, conversational access to Boston's open data.

Boston Core MCP is a Model Context Protocol (MCP) server created by the City of Boston Department of Innovation and Technology (DoIT). It gives AI assistants and agentic tools safe, read-only access to Boston's open data portal, enabling staff, residents, and partners to explore civic information through natural conversation.

Why Boston Core MCP?

For City Staff

• Ask questions naturally - "What datasets do we have about 311 requests?" or "Show me crime data from last month"
• No technical barriers - Works directly with Claude Desktop and other MCP-compatible tools
• Always up-to-date - Connects directly to Boston's live open data portal
• Save time - Get answers instantly without navigating complex data portals

For Residents & Partners

• Explore Boston's data through conversation instead of navigating complex portals
• Discover datasets you didn't know existed
• Get answers quickly without learning database queries or API syntax
• Trustworthy source - Direct connection to official City of Boston data

For Developers

• Production-ready - Deployed on AWS Lambda with automated CI/CD
• Well-documented - Comprehensive guides for deployment and development
• Open source - MIT licensed, built with modern Python and best practices
• Extensible - Easy to adapt for other cities or data sources

What It Does

Boston Core MCP provides five powerful tools that let AI assistants interact with Boston's open data:

1. Search Datasets - Find datasets by keywords (e.g., "311", "crime", "parking")
2. List All Datasets - Browse everything available on the portal
3. Get Dataset Info - Detailed metadata and resources for any dataset
4. Query Data - Get actual data records with filtering, sorting, and pagination
5. Get Schema - Understand the structure of any dataset

Quick Start

Connect Claude Desktop (2 minutes)

The server is already deployed and ready to use:

# Install mcpengine
pipx install 'mcpengine[cli]'

# Connect Claude to Boston OpenData
mcpengine proxy boston-opendata-lambda \
  https://kdbjj7ebdewlcy24bt4wbf3uju0tjgdf.lambda-url.us-east-1.on.aws \
  --mode http --claude

Then open Claude Desktop and start asking questions about Boston's data!

📖 Full setup guide: docs/LAMBDA_QUICKSTART.md

Key Features

Safety First

• Read-only access - No modifications to Boston's data
• Enforced limits - Timeouts and record limits prevent abuse
• Input validation - All queries validated before execution
• Error handling - Comprehensive error handling and retry logic

Production Ready

• Deployed on AWS Lambda - Scalable, serverless infrastructure
• Automated CI/CD - GitHub Actions for testing and deployment
• Monitoring - CloudWatch logs and structured logging
• Cost-effective - Typically $2-8/month for moderate usage

Developer Friendly

• Well-documented - Guides for every use case
• Type-safe - Built with Python type hints and Pydantic
• Tested - Test suite included
• Modern stack - Python 3.10+, MCPEngine, Terraform

Use Cases

City Staff

• Policy Research: "What datasets track housing permits in the last year?"
• Data Analysis: "Show me 311 service requests about potholes from this month"
• Quick Lookups: "What's the structure of the crime incident reports dataset?"

Residents

• Civic Engagement: "What data is available about public transportation?"
• Research: "Find datasets related to city budget and spending"
• Exploration: "What open data does Boston publish?"

Developers & Researchers

• API Discovery: "What resources are available in the 311 dataset?"
• Data Exploration: "Query the first 100 records from crime incidents"
• Schema Understanding: "Show me the schema for parking violations"

Documentation

Getting Started

• [Quick Start Guide](docs/LAMBDA_QUICKSTART.md) - Connect Claude Desktop in minutes
• [Local Development](docs/LOCAL_DEVELOPMENT.md) - Run and develop locally

Deployment & Operations

• [Lambda Deployment](docs/LAMBDA_DEPLOYMENT.md) - Complete deployment guide
• [Terraform Infrastructure](docs/TERRAFORM_DEPLOYMENT.md) - Infrastructure as code
• [CI/CD Pipeline](docs/CI_CD_GUIDE.md) - Automated testing and deployment
• [Workflows Reference](docs/WORKFLOWS.md) - GitHub Actions quick reference

Architecture & Development

• [Development Guide](docs/DEVELOPMENT.md) - Architecture and design decisions

Technology Stack

• Python 3.10+ - Modern Python with type hints
• MCPEngine - HTTP-based MCP server framework
• AWS Lambda - Serverless compute
• Terraform - Infrastructure as code
• GitHub Actions - CI/CD automation

Community & Support

This project is maintained by the City of Boston Department of Innovation and Technology (DoIT).

• Issues: Open an issue for bugs or feature requests
• Contributions: See CONTRIBUTORS.md for guidelines
• License: MIT License - see LICENSE

Learn More

• Boston Open Data Portal: data.boston.gov
• Model Context Protocol: modelcontextprotocol.io
• MCPEngine: Featureform MCPEngine

Authors

Srihari Raman & Pradhu Balamurugan

Built with ❤️ by the City of Boston DoIT team