Zig MCP Server

Modern Zig AI 10x dev assistant with comprehensive build system support

A powerful Model Context Protocol (MCP) server that provides comprehensive Zig language assistance, including modern build system support, code optimization, and best practices guidance.

🚀 What's New in v0.2.0+

• 🏗️ Zig 0.15.2+ Support: Fully updated with modern b.path() and root_module patterns

• 📦 Enhanced Module System: Support for latest module system with root_module.addImport()

• 🔄 Migration Guidance: Automated detection and upgrade suggestions for legacy patterns

• 🔧 Enhanced Code Analysis: Improved optimization suggestions and modern pattern detection

• 🧪 Comprehensive Testing: 85+ test cases with full coverage reporting

• ⚡ Better Code Quality: Fixed all TypeScript compilation errors and linting issues

• 📚 Extended Documentation: Complete Zig 0.15.2+ build system guide with migration tips

Related MCP server: Hi-AI

🛠️ Features

🏗️ Build System Tools (NEW!)

1. Build System Generation (generate_build_zig)

Generate modern build.zig files with Zig 0.15.2+ patterns:

• Cross-compilation support with latest target options

• Modern dependency management with build.zig.zon

• Test and documentation integration

• Enhanced module system support

2. Build System Analysis (analyze_build_zig)

Analyze existing build files and get modernization recommendations:

• Detect deprecated patterns

• Suggest Zig 0.15.2+ alternatives

• Identify missing best practices

• Module system migration guidance

3. Dependency Management (generate_build_zon)

Generate build.zig.zon files for modern package management:

• Popular Zig packages catalog

• Version management guidance

• Best practices documentation

Features

Tools

1. Code Optimization (optimize_code)

Enhanced with modern Zig patterns and build mode analysis:

• Debug, ReleaseSafe, ReleaseFast, ReleaseSmall

• Modern optimization suggestions

• Zig 0.12+ pattern recommendations

// Example usage
{
  "code": "const std = @import(\"std\");\n...",
  "optimizationLevel": "ReleaseFast"
}

2. Compute Units Estimation (estimate_compute_units)

Estimates computational complexity and resource usage of Zig code:

• Memory usage analysis

• Time complexity estimation

• Allocation patterns detection

// Example usage
{
  "code": "const std = @import(\"std\");\n..."
}

3. Code Generation (generate_code)

Generates Zig code from natural language descriptions with support for:

• Error handling

• Testing

• Performance optimizations

• Documentation

// Example usage
{
  "prompt": "Create a function that sorts an array of integers",
  "context": "Should handle empty arrays and use comptime when possible"
}

4. Code Recommendations (get_recommendations)

Provides code improvement recommendations and best practices:

• Style and conventions

• Design patterns

• Safety considerations

• Performance insights

// Example usage
{
  "code": "const std = @import(\"std\");\n...",
  "prompt": "Improve performance and safety"
}

Resources

1. Language Reference (zig://docs/language-reference)

   • Official Zig language documentation

   • Syntax and features guide

   • Best practices

2. Standard Library Documentation (zig://docs/std-lib)

   • Complete std library reference

   • Function signatures and usage

   • Examples and notes

3. Popular Repositories (zig://repos/popular)

   • Top Zig projects on GitHub

   • Community examples and patterns

   • Real-world implementations

Installation

Installing via Smithery

To install Zig MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install zig-mcp-server --client claude

Manual Installation

1. Clone the repository:

git clone [repository-url]
cd zig-mcp-server

2. Install dependencies:

npm install

3. Build the server:

npm run build

4. Configure environment variables:

# Create a GitHub token for better API rate limits
# https://github.com/settings/tokens
# Required scope: public_repo
GITHUB_TOKEN=your_token_here

5. Add to MCP settings:

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

Usage Examples

1. Optimize Code

const result = await useMcpTool("zig", "optimize_code", {
  code: `
    pub fn fibonacci(n: u64) u64 {
        if (n <= 1) return n;
        return fibonacci(n - 1) + fibonacci(n - 2);
    }
  `,
  optimizationLevel: "ReleaseFast"
});

2. Estimate Compute Units

const result = await useMcpTool("zig", "estimate_compute_units", {
  code: `
    pub fn bubbleSort(arr: []i32) void {
        var i: usize = 0;
        while (i < arr.len) : (i += 1) {
            var j: usize = 0;
            while (j < arr.len - 1) : (j += 1) {
                if (arr[j] > arr[j + 1]) {
                    const temp = arr[j];
                    arr[j] = arr[j + 1];
                    arr[j + 1] = temp;
                }
            }
        }
    }
  `
});

3. Generate Code

const result = await useMcpTool("zig", "generate_code", {
  prompt: "Create a thread-safe counter struct",
  context: "Should use atomic operations and handle overflow"
});

4. Get Recommendations

const result = await useMcpTool("zig", "get_recommendations", {
  code: `
    pub fn main() !void {
        var list = std.ArrayList(u8).init(allocator);
        var i: u32 = 0;
        while (true) {
            if (i >= 100) break;
            try list.append(@intCast(i));
            i += 1;
        }
    }
  `,
  prompt: "performance"
});

Development

Project Structure

zig-mcp-server/
├── src/
│   └── index.ts    # Main server implementation
├── build/          # Compiled JavaScript
├── package.json    # Dependencies and scripts
└── tsconfig.json   # TypeScript configuration

Building

# Development build with watch mode
npm run watch

# Production build
npm run build

Testing

npm test

Contributing

1. Fork the repository

2. Create your feature branch (git checkout -b feature/amazing-feature)

3. Commit your changes (git commit -m 'Add some amazing feature')

4. Push to the branch (git push origin feature/amazing-feature)

5. Open a Pull Request

License

MIT License - see the LICENSE file for details.