CourtListener MCP Server
Enables LLM-friendly access to the CourtListener legal database and eCFR for searching legal opinions, court cases, judges, documents, and federal regulations.
README
CourtListener MCP Server
A Model Context Protocol (MCP) server that provides LLM-friendly access to the CourtListener legal database and the Electronic Code of Federal Regulations (eCFR) through the official CourtListener API v4. This server enables searching and retrieving legal opinions, court cases, judges, legal documents, and federal regulations for precise legal research and citation verification.
๐ฏ Purpose
The CourtListener MCP Server provides comprehensive access to legal case data, court opinions, and federal regulations through the extensive CourtListener and eCFR databases. CourtListener contains millions of legal opinions from federal and state courts, while eCFR provides up-to-date federal regulations.
๐ Key Advantages
- Comprehensive Legal Database:
- Access to millions of court opinions and legal decisions
- Federal and state court coverage
- Real-time updates from court systems
- Full Text Content:
- Complete opinion text for citation verification
- Structured legal document organization
- Rich metadata including judges, courts, and dates
- Regulatory Research:
- Search and retrieve current federal regulations
- Validate regulatory citations and references
- Legal Research:
- Search by judge, court, case name, or content
- Verify exact legal language and precedents
- Validate legal citations and references
๐ ๏ธ Available MCP Tools
The CourtListener MCP Server provides these production-ready tools (see app/README.md for full details and parameters):
- Opinion & Case Search:
search_opinionsโ Search legal opinions and court decisionssearch_docketsโ Search court cases and docketssearch_dockets_with_documentsโ Search dockets with nested documentssearch_recap_documentsโ Search RECAP filing documentssearch_audioโ Search oral argument audiosearch_peopleโ Search judges and legal professionals
- Entity Retrieval:
get_opinion,get_docket,get_audio,get_court,get_person,get_cluster
- Citation & Regulation Tools:
lookup_citation,batch_lookup_citations,verify_citation_format,parse_citation_with_citeurl,extract_citations_from_text,enhanced_citation_lookuplist_titles,list_agencies,search_regulations,list_all_corrections,list_corrections_by_title,get_search_suggestions,get_search_summary,get_title_search_counts,get_daily_search_counts,get_ancestry,get_title_structure,get_source_xml,get_source_json
- System & Health:
status,get_api_status,health_check
See app/README.md for a full reference of all tools, parameters, and usage examples.
๐ฆ Installation
Prerequisites
- Python 3.12+
- uv for dependency management
- Internet connection for CourtListener API access
Install with uv
# Clone the repository
git clone <repository-url>
cd CourtListener
# Install dependencies
uv sync
# Activate the environment (optional)
uv shell
Environment Configuration
Create a .env file in the project root:
COURTLISTENER_BASE_URL=https://www.courtlistener.com/api/rest/v4/
COURT_LISTENER_TIMEOUT=30
LOG_LEVEL=INFO
RATE_LIMIT_REQUESTS=10
RATE_LIMIT_PERIOD=60
DEBUG=false
MCP_PORT=8765
MCP_DEV_PORT=8766
Running the Server
The server now runs with streamable-http transport by default:
uv run python -m app.server
This will start the server at:
- Host:
0.0.0.0(accessible from external connections) - Port:
8000 - Endpoint:
http://localhost:8000/mcp/
Or use the VS Code task: Run MCP Server
Connecting to the Server
When using the streamable-http transport, clients can connect to the server using:
from fastmcp import Client
async with Client("http://localhost:8000/mcp/") as client:
result = await client.call_tool("status")
print(result)
๐ก Usage Examples
See app/README.md for detailed tool usage and examples, including search, citation, and regulatory queries.
๐ณ Docker Setup
# Production
docker-compose up -d
# Development with hot reload
docker-compose --profile dev up --build
๐งช Testing
uv run pytest
uv run pytest --cov=app --cov-report=term-missing
See tests/README.md for test suite details, coverage, and troubleshooting.
๐ง Development
uv run ruff format .
uv run ruff check .
uv run mypy app/
uv run pip-audit
๐จ Troubleshooting
See app/README.md and tests/README.md for troubleshooting and advanced usage.
๐ Documentation
- Source Code Documentation
- Test Documentation
- Project Context
- CourtListener API Documentation
- eCFR API Documentation
- FastMCP Framework
- Model Context Protocol
Ready to use! The CourtListener MCP Server provides production-ready access to federal regulations and legal data through 20+ comprehensive MCP tools.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.