mcp-graphql-tools and github_graphql_api_mcp

These tools are competitors, as both implement a Model Control Protocol (MCP) server for AI assistants to interact with GraphQL APIs, differing in their specific GraphQL target (generic vs. GitHub-specific).

mcp-graphql-tools
35
Emerging
github_graphql_api_mcp
28
Experimental
Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 15/25
Maintenance 6/25
Adoption 3/25
Maturity 7/25
Community 12/25
Stars: 8
Forks: 4
Downloads:
Commits (30d): 0
Language: JavaScript
License: MIT
Stars: 4
Forks: 1
Downloads:
Commits (30d): 0
Language: Python
License:
Stale 6m No Package No Dependents
No License No Package No Dependents

About mcp-graphql-tools

saewoohan/mcp-graphql-tools

GraphQL MCP server for AI assistants

Exposes two core tools for GraphQL interaction: `graphql_query` for executing queries/mutations with optional variables and custom headers, and `graphql_introspect` for schema exploration. Implements query complexity limiting and configurable timeouts to prevent abuse, with support for Claude Desktop integration via stdio transport and pre-configured endpoints through command-line arguments.

About github_graphql_api_mcp

wanzunz/github_graphql_api_mcp

A Model Control Protocol (MCP) server for exploring the GitHub GraphQL schema and executing optimized queries. Provides AI assistants with efficient GitHub data retrieval capabilities through GraphQL.

Implements schema introspection tools that enable AI assistants to dynamically discover GitHub GraphQL capabilities without predefined tool definitions, while executing single optimized queries that fetch multiple related resources in one request rather than chaining sequential API calls. Built as an MCP server using Python with stdio transport, it reduces token consumption by allowing precise field selection through GraphQL instead of receiving full REST API responses. Integrates directly with Claude and other MCP-compatible AI clients, positioning itself as a lightweight alternative to REST-based GitHub integrations that require frequent round-trips and context-heavy intermediate outputs.

Scores updated daily from GitHub, PyPI, and npm data. How scores work