DocketBird MCP Server

Name: DocketBird MCP Server
Author: gravix-db

@gravix-db

Repository

About DocketBird MCP Server

MCP server for APIs hosted by DocketBird.

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "docketbird-mcp": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Tools

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Overview

What is DocketBird MCP Server?

DocketBird MCP Server is an MCP server that provides access to DocketBird’s court case data and document management functionality. It is intended for developers and legal professionals who need to query case information, download documents, and manage court data through the Model Context Protocol.

How to use DocketBird MCP Server?

Install uv and dependencies, set the DOCKETBIRD_API_KEY environment variable, then run the server with either uv run docketbird_mcp.py --transport stdio or --transport sse. Configure the MCP client by adding the server configuration to the appropriate JSON file (e.g., ~/.cursor/mcp.json or ~/Library/Application Support/Claude/claude_desktop_config.json).

Key features of DocketBird MCP Server

Retrieve comprehensive case details and documents.
Download specific documents by DocketBird ID.
List cases belonging to an account.
List all available courts and case types.
Supports both stdio and SSE transports.
Docker deployment for cloud servers.

Use cases of DocketBird MCP Server

Querying details for a specific court case (e.g., “txnd-3:2007-cv-01697”).
Downloading a particular document from a case using its DocketBird ID.
Listing all cases associated with a user account.
Exploring available courts and case types before filing.
Deploying the server to a cloud environment for team access.

FAQ from DocketBird MCP Server

What are the runtime requirements?

Python 3.11 and the uv package manager are required.

How do I obtain an API key?

You need a DocketBird API key, set as the DOCKETBIRD_API_KEY environment variable.

Does the server support remote access?

Yes, it can be run with SSE transport and deployed to a cloud server using Docker.

What transport types are available?

The server supports both stdio (for local clients) and SSE (for remote connections).

Is there a prototype agent available?

Yes, a prototype agent (db_agent_prototype.py) is included that uses OpenAI’s GPT-4.1 to interact with the server via natural language.

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