zig-mcp
MCP server for Zig that connects AI coding assistants to ZLS (Zig Language Server) via LSP — 16 tools for code intelligence, build, and test.
zig-mcp
MCP server for Zig that connects AI coding assistants to ZLS via the Language Server Protocol.
Works with Claude Code, Cursor, Windsurf, and any MCP-compatible client.
AI assistant <--(MCP stdio)--> zig-mcp <--(LSP pipes)--> ZLS
|
zig build / test / check
Requirements
Install
Claude Code plugin (recommended)
Install directly from the Claude Code interface — no manual build needed:
# 1. Add the marketplace
/plugin marketplace add nzrsky/zig-mcp
# 2. Install the plugin
/plugin install zig-mcp@zig
Or as a one-liner from the terminal:
claude plugin marketplace add nzrsky/zig-mcp && claude plugin install zig-mcp@zig
The binary is built automatically on first use. Just make sure zig and zls are in your PATH.
Manual build
git clone https://github.com/nzrsky/zig-mcp.git
cd zig-mcp
zig build -Doptimize=ReleaseFast
Binary is at zig-out/bin/zig-mcp.
Setup (manual install only)
If you installed via the plugin system, skip this section — everything is configured automatically.
Claude Code
# add globally
claude mcp add zig-mcp -- /absolute/path/to/zig-mcp --workspace /path/to/your/zig/project
# add for current project only
claude mcp add --scope project zig-mcp -- /absolute/path/to/zig-mcp --workspace /path/to/your/zig/project
Or edit ~/.claude/mcp_servers.json:
{
"mcpServers": {
"zig-mcp": {
"command": "/absolute/path/to/zig-mcp",
"args": ["--workspace", "/path/to/your/zig/project"]
}
}
}
If you omit
--workspace, zig-mcp uses the current working directory.
Cursor
Add to .cursor/mcp.json in your project:
{
"mcpServers": {
"zig-mcp": {
"command": "/absolute/path/to/zig-mcp",
"args": ["--workspace", "/path/to/your/zig/project"]
}
}
}
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"zig-mcp": {
"command": "/absolute/path/to/zig-mcp",
"args": ["--workspace", "/path/to/your/zig/project"]
}
}
}
Options
--workspace, -w <path> Project root directory (default: cwd)
--zls-path <path> Path to ZLS binary (default: auto-detect from PATH)
--help, -h Show help
--version Show version
Tools
Code intelligence (via ZLS)
| Tool | What it does |
|---|---|
zig_hover | Type info and docs for a symbol |
zig_definition | Go to definition |
zig_references | Find all references |
zig_completion | Completion suggestions |
zig_diagnostics | Errors and warnings for a file |
zig_format | Format a file |
zig_rename | Rename a symbol across the workspace |
zig_document_symbols | List all symbols in a file |
zig_workspace_symbols | Search symbols across the project |
zig_code_action | Quick fixes and refactors for a range |
zig_signature_help | Function signature at cursor |
Build & run
| Tool | What it does |
|---|---|
zig_build | Run zig build with optional args |
zig_test | Run tests (whole project or single file, with optional filter) |
zig_check | Run zig ast-check on a file |
zig_version | Show Zig and ZLS versions |
zig_manage | Manage Zig versions via zvm |
How it works
zig-mcp spawns ZLS as a child process and talks to it over stdin/stdout using the LSP protocol (Content-Length framing). On the other side, it speaks MCP (newline-delimited JSON-RPC) to the AI assistant.
Three threads:
- main -- reads MCP requests, dispatches tool calls, writes responses
- reader -- reads LSP responses from ZLS, correlates by request ID
- stderr -- forwards ZLS stderr to the server log
If ZLS crashes, zig-mcp automatically restarts it and re-opens all tracked documents.
Files are opened in ZLS lazily on first access -- no need to manage document state manually.
Development
# build
zig build
# run tests (~75 unit tests)
zig build test
# run manually
echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"capabilities":{}}}' | \
zig-out/bin/zig-mcp --workspace . 2>/dev/null
License
MIT
相關伺服器
Scout Monitoring MCP
贊助Put performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
贊助Access financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
SSH Server MCP
An MCP server that provides SSH-based remote management tools, acting as proxy
DocsetMCP
A server for accessing Dash-style documentation sets locally. Requires a local Dash installation.
PAMPA
An MCP server for intelligent semantic search and automatic learning within codebases, allowing AI agents to efficiently query and index project artifacts.
Elementor MCP Server
Perform CRUD operations on Elementor page data for a target WordPress website.
FastMCP ThreatIntel
An AI-powered threat intelligence analysis tool for multi-source IOC analysis, APT attribution, and interactive reporting.
Dify Server
Integrates the Dify AI API to generate Ant Design business component code. Supports text, image inputs, and streaming responses.
Creatify
MCP Server that exposes Creatify AI API capabilities for AI video generation, including avatar videos, URL-to-video conversion, text-to-speech, and AI-powered editing tools.
MCP Simple OpenAI Assistant
A simple server for interacting with OpenAI assistants using an API key.
SynapseForge
A server for systematic AI experimentation and prompt A/B testing.
Node.js Sandbox MCP Server
Run arbitrary JavaScript in an isolated Docker container with on-the-fly npm dependency installation.