mcp-gopls — MCP Server by hloiseau

by hloiseau · MCP Server · ★ 88

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About mcp-gopls

mcp-gopls – MCP server for Go (gopls) A Model Context Protocol (MCP) server that lets AI assistants use Go’s LSP () for navigation, diagnostics, testing, coverage, and more. TL;DR: If you use Claude / Cursor / Copilot with Go, gives the AI full LSP powers: go-to-definition, references, hover, completion, , coverage, , , etc. Overview This MCP server helps AI assistants to: Use LSP to analyze Go workspaces Navigate to definitions, references, and workspace symbols Format, rename, and inspect code actions without leaving MCP Run Go tests, coverage, , , and module graph commands with structured results Read workspace resources (overview + go.mod) and consume curated prompts Status: Actively developed – used in real projects. Tested with Go 1.25.x and . Architecture This project uses the mark3labs/mcp-go library

ai-agentsai-toolsdeveloper-toolsgogolanggoplslspmcpmodel-context-protocol

Quick Facts

Stars88
Forks12
LanguageGo
CategoryMCP Server
LicenseApache-2.0
Quality Score77.4770162940069/100
Open Issues8
Last Updated2026-06-22
Created2025-04-05
Platformsgo, mcp
Est. Tokens~20k

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Frequently Asked Questions

What is mcp-gopls?

mcp-gopls is Model Context Protocol (MCP) server for Go using gopls – LSP-powered analysis, tests, coverage, and tooling.. It is categorized as a MCP Server with 88 GitHub stars.

What programming language is mcp-gopls written in?

mcp-gopls is primarily written in Go. It covers topics such as ai-agents, ai-tools, developer-tools.

How do I install or use mcp-gopls?

You can find installation instructions and usage details in the mcp-gopls GitHub repository at github.com/hloiseau/mcp-gopls. The project has 88 stars and 12 forks, indicating an active community.

What license does mcp-gopls use?

mcp-gopls is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to mcp-gopls?

The top alternatives to mcp-gopls on Agent Skills Hub include agent-lsp, agent-deck, flyto-core. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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