DocketBird MCP Server

DocketBird MCP Server

Enables searching and downloading court documents, listing cases, and retrieving case details via the DocketBird API. It supports secure OAuth 2.0 authentication for remote access and a standard local mode for personal use.

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README

DocketBird MCP Server

An MCP server for searching and downloading court documents via the DocketBird API. Deployed on DigitalOcean with Docker, using OAuth 2.0 so each user brings their own DocketBird API key.

Tools

Tool Description
docketbird_get_case_details Get case info, parties, and paginated documents
docketbird_search_documents Search documents within a case by keyword
docketbird_list_cases List cases for company or user scope
docketbird_list_courts Get court codes and case types
docketbird_download_document Download a single document by ID
docketbird_download_files Download all available documents for a case

Requirements

  • Python 3.11
  • uv package manager

Setup

  1. Install uv:
curl -LsSf https://astral.sh/uv/install.sh | sh
  1. Create and activate a virtual environment:
uv venv
source .venv/bin/activate
  1. Install dependencies:
uv pip install -r requirements.txt

Running the Server

# stdio transport (uses DOCKETBIRD_API_KEY env var, no OAuth)
DOCKETBIRD_API_KEY="your-key" python docketbird_mcp.py --transport stdio

# HTTP transport with OAuth (Streamable HTTP at /mcp)
python docketbird_mcp.py --transport http
# Then visit http://localhost:8080/signup to create an account

Connecting to the Deployed Server

See DocketBird_MCP_Installation_Guide.pdf for the full walkthrough with screenshots.

Quick version

  1. Register at https://app.docketbird-mcp.com/signup with your email, password, and DocketBird API key
  2. In Claude.ai or Claude Desktop, add a remote MCP server with URL https://app.docketbird-mcp.com/mcp
  3. Claude auto-discovers OAuth, redirects you to log in, and connects

Stdio (local development)

For Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json) or Cursor (~/.cursor/mcp.json):

{
  "mcpServers": {
    "docketbird-mcp": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/path/to/docketbird-mcp-plus",
        "python",
        "docketbird_mcp.py"
      ],
      "env": {
        "DOCKETBIRD_API_KEY": "YOUR_KEY"
      }
    }
  }
}

Authentication

The server uses OAuth 2.0 with PKCE for HTTP mode. Each user registers with their own DocketBird API key, which is stored server-side and attached to OAuth tokens. The SDK handles the protocol endpoints automatically:

  • /.well-known/oauth-authorization-server - OAuth metadata discovery
  • /register - Dynamic Client Registration
  • /authorize - Authorization endpoint (redirects to /login)
  • /token - Token exchange and refresh

In stdio mode, the DOCKETBIRD_API_KEY env var is used directly (no OAuth).

Security

  • OAuth 2.0 with PKCE (no shared API key on the server)
  • Per-user DocketBird API keys stored in SQLite with bcrypt-hashed passwords
  • Rate limiting: 30 requests per 60 seconds per IP
  • HTTPS-only downloads with SSRF domain allowlist
  • Path traversal protection on file downloads
  • Container runs as non-root mcpuser
  • GitHub Actions pinned to commit SHAs
  • Dependencies pinned to exact versions

Deployment

Deployed via Docker and GitHub Actions. Pushes to main trigger automatic deployment.

  • Domain: app.docketbird-mcp.com
  • Docker volume: docketbird-data at /app/data (SQLite auth database)
  • Health check: https://app.docketbird-mcp.com/health
  • Caddy reverse proxy handles HTTPS (Let's Encrypt)

Local Docker Build

docker build -t docketbird-mcp:latest .

docker run -d \
  --name docketbird-mcp \
  --restart=always \
  -e SERVER_URL="http://localhost:8040" \
  -v docketbird-data:/app/data \
  -p 8040:8080 \
  docketbird-mcp:latest

Reference Data

  • courts.json - Court codes and names
  • case_types.json - Case type abbreviations and examples

Acknowledgment

This project is built upon the original docketbird-mcp developed in conjunction with @federicoburman and the Gravix.AI team.

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