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Model Context Protocol (MCP) Server for GraphQL Policies API

@Ad-Veritas

Repository

About Model Context Protocol (MCP) Server for GraphQL Policies API

Model Context Protocol (MCP) server to access an instance of TrueRAG

Basic information

Category

Developer Tools

Runtime

jupyter notebook

Transports

stdio

Publisher

Ad-Veritas

Config

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

{
  "mcpServers": {
    "shipping-policies": {
      "command": "uv",
      "args": [
        "--directory",
        "{path_to_mcp_server}/mcp-server-trueRAG",
        "run",
        "fastmcp",
        "run",
        "server.py"
      ],
      "env": {
        "GRAPHQL_API_KEY": "",
        "GRAPHQL_ENDPOINT": ""
      }
    }
  }
}

Tools

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Overview

What is Model Context Protocol (MCP) Server for GraphQL Policies API?

It is an MCP server that provides access to policies via a GraphQL API, built using the Python MCP SDK and the GQL library. It is intended for users of TrueRAG systems who need to query policy data through a standardized model context protocol interface.

How to use Model Context Protocol (MCP) Server for GraphQL Policies API?

Clone the repository, ensure uv is installed, create a .env file with GRAPHQL_API_KEY and GRAPHQL_ENDPOINT from your TrueRAG environment, then configure your MCP client (e.g., Claude Desktop) using the uv --directory ... run fastmcp run server.py command as described in the README.

Key features of Model Context Protocol (MCP) Server for GraphQL Policies API

  • Built with Python MCP SDK and GQL library
  • Uses uv for dependency management and execution
  • Connects to GraphQL APIs for TrueRag systems
  • Configurable via environment variables for API key and endpoint
  • Provides access to policies through a standardized interface

Use cases of Model Context Protocol (MCP) Server for GraphQL Policies API

  • Querying policies from a TrueRAG system via Claude Desktop
  • Integrating policy data into AI workflows using MCP
  • Automating policy retrieval with AI assistants

FAQ from Model Context Protocol (MCP) Server for GraphQL Policies API

What dependencies are required?

Python, uv, and the GQL library (managed automatically by uv).

How do I configure the server?

Set the GRAPHQL_API_KEY and GRAPHQL_ENDPOINT environment variables in a .env file placed in the repository root.

What MCP clients are supported?

The README provides a configuration example for Claude Desktop, but any MCP‑compatible client can be used.

Where does the data come from?

Data is accessed via a GraphQL API from a TrueRAG environment; the API key and endpoint must be supplied by the user.

What runtime environment is needed?

The server requires uv to run the fastmcp command; no other runtime or container is explicitly required.

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