Overview

The Zig MCP Server is a powerful Model Context Protocol (MCP) server that provides comprehensive Zig language assistance, including modern build system support, code optimization, and best practices guidance. It enhances AI capabilities with Zig-specific functionality like code optimization, compute unit estimation, and code generation.

Developed by:

Developed by openSVM

Key Features

🏗️

Modern Build System Support

Generate and analyze build.zig files with Zig 0.12+ patterns

⚡

Code Optimization

Enhanced with modern Zig patterns and build mode analysis

📝

Code Generation

Generates Zig code from natural language descriptions

📊

Compute Units Estimation

Estimates computational complexity and resource usage of Zig code

Available Tools

Quick Reference

Tool	Purpose	Category
`generate_build_zig`	Generate `build.zig` files	Build System
`analyze_build_zig`	Analyze existing `build.zig` files	Build System
`generate_build_zon`	Generate `build.zig.zon` files	Dependency Management
`optimize_code`	Optimize Zig code	Code Analysis
`estimate_compute_units`	Estimate code complexity and resource usage	Code Analysis
`generate_code`	Generate Zig code from natural language	Code Generation
`get_recommendations`	Provide code improvement recommendations	Best Practices

Detailed Usage

generate_build_zig▶

Generate modern build.zig files with Zig 0.12+ patterns.

use_mcp_tool({
  server_name: "zig",
  tool_name: "generate_build_zig",
  arguments: {
    projectName: "my_zig_project",
    target: "native",
    dependencies: ["zlib", "sdl"]
  }
});

optimize_code▶

Optimize Zig code with modern Zig patterns and build mode analysis.

use_mcp_tool({
  server_name: "zig",
  tool_name: "optimize_code",
  arguments: {
    code: "const std = @import(\"std\");\n...",
    optimizationLevel: "ReleaseFast"
  }
});

estimate_compute_units▶

Estimates computational complexity and resource usage of Zig code.

use_mcp_tool({
  server_name: "zig",
  tool_name: "estimate_compute_units",
  arguments: {
    code: "const std = @import(\"std\");\n..."
  }
});

generate_code▶

Generates Zig code from natural language descriptions.

use_mcp_tool({
  server_name: "zig",
  tool_name: "generate_code",
  arguments: {
    prompt: "Create a function that sorts an array of integers",
    context: "Should handle empty arrays and use comptime when possible"
  }
});

Installation

{
  "mcpServers": {
    "zig": {
      "command": "node",
      "args": [
        "/path/to/zig-mcp-server/build/index.js"
      ],
      "env": {
        "GITHUB_TOKEN": "your_github_token",
        "NODE_OPTIONS": "--experimental-vm-modules"
      },
      "restart": true
    }
  }
}

GitHub Token:

Create a GitHub token with public_repo scope for better API rate limits.

Sources

Elasticsearch MCP Server

Elasticsearch MCP servers enable AI models to interact with Elasticsearch, providing capabilities for searching documents, analyzing indices, and managing clusters.

Git MCP Server

Git MCP servers enable AI models to interact with Git version control systems, providing capabilities for repository management, branch operations, commit handling, and collaborative development workflows.

Redis MCP Server

Redis MCP servers enable AI models to interact with Redis databases, providing capabilities for key-value operations, caching, pub/sub messaging, and high-performance data structures.

Zig MCP Server