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mrjoshuak/godoc-mcp

by Various

MCP server that reduces LLM context usage when AI coding agents work with Go — structured documentation instead of source-file dumps.

M

MCP

mrjoshuak/godoc-mcp

Added 1 June 2026

#ai-agents #ai-tools #anthropic #claude #documentation #golang #llm #llm-tools

Overview

MCP server that reduces LLM context usage when AI coding agents work with Go. It provides structured documentation instead of source-file dumps.

Best for

Best for
Developers using AI coding agents with Go projects to minimize context overhead

Use cases

  • Feeding Go package documentation to MCP-compatible AI agents
  • Reducing token usage during Go codebase analysis in LLMs
  • Replacing source file dumps with compact doc summaries for coding assistants

Notes

MCP server that reduces LLM context usage when AI coding agents work with Go. It provides structured documentation instead of source-file dumps.

120 stars on GitHub. Last updated 2026-03-06. Licensed MIT.

Use cases

  • Feeding Go package documentation to MCP-compatible AI agents
  • Reducing token usage during Go codebase analysis in LLMs
  • Replacing source file dumps with compact doc summaries for coding assistants

Pros

  • Efficiently lowers token consumption for LLM interactions with Go code
  • Structured documentation output improves relevance over raw source
  • Lightweight MCP server written in Go for easy integration

Cons

  • Limited to Go documentation only; no support for other languages
  • Requires MCP protocol support in the AI agent or client
  • May miss implementation details not covered in documentation

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

Pros

  • Efficiently lowers token consumption for LLM interactions with Go code
  • Structured documentation output improves relevance over raw source
  • Lightweight MCP server written in Go for easy integration

Cons

  • Limited to Go documentation only; no support for other languages
  • Requires MCP protocol support in the AI agent or client
  • May miss implementation details not covered in documentation