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UnitVectorY-Labs/mcp-graphql-forge

by Various

A lightweight, configuration-driven MCP server that exposes curated GraphQL queries as modular tools, enabling intentional API interactions from your agents.

U

MCP

UnitVectorY-Labs/mcp-graphql-forge

Added 1 June 2026

#go #graphql #mcp-server

Overview

A lightweight MCP server written in Go that exposes curated GraphQL queries as modular tools. It uses a configuration-driven approach to limit agents to intentional API interactions rather than arbitrary GraphQL requests.

Best for

Best for
Developers building MCP-based agents that need controlled, intentional access to GraphQL APIs

Use cases

  • Providing AI agents with safe access to specific GraphQL queries
  • Integrating GraphQL APIs into MCP-compatible agent workflows
  • Exposing pre-defined query endpoints as reusable agent tools

How to use

Install

go install github.com/UnitVectorY-Labs/mcp-graphql-forge@latest

Tools exposed

  • annotations
  • readOnlyHint
  • destructiveHint
  • idempotentHint
  • openWorldHint

Example client config

name: "ExampleServer"\nurl: "https://api.github.com/graphql"\ntoken_command: "gh auth token"

Notes

A lightweight MCP server written in Go that exposes curated GraphQL queries as modular tools. It uses a configuration-driven approach to limit agents to intentional API interactions rather than arbitrary GraphQL requests.

4 stars on GitHub. Last updated 2026-05-30. Licensed MIT.

Use cases

  • Providing AI agents with safe access to specific GraphQL queries
  • Integrating GraphQL APIs into MCP-compatible agent workflows
  • Exposing pre-defined query endpoints as reusable agent tools

Pros

  • Lightweight and easy to deploy with Go binary
  • Configuration-driven setup reduces boilerplate
  • Curated query model minimizes risk of accidental harmful requests

Cons

  • Only supports predefined queries, not arbitrary GraphQL
  • Requires a GraphQL endpoint and manual query curation
  • Small community and limited ecosystem (4 stars)

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Lightweight and easy to deploy with Go binary
  • Configuration-driven setup reduces boilerplate
  • Curated query model minimizes risk of accidental harmful requests

Cons

  • Only supports predefined queries, not arbitrary GraphQL
  • Requires a GraphQL endpoint and manual query curation
  • Small community and limited ecosystem (4 stars)
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