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zig-mcp-server

MCP.Pizza Chef: openSVM

The zig-mcp-server is a Model Context Protocol server providing advanced Zig language tooling. It offers code optimization at multiple levels, computational resource estimation, and Zig code generation. This server supports developers by analyzing code for performance, memory usage, and best practices, enabling AI models to interact with Zig codebases effectively and improve code quality and efficiency.

Use This MCP server To

Optimize Zig code for different build configurations Estimate memory and time complexity of Zig functions Generate Zig code snippets from specifications Analyze allocation patterns in Zig programs Provide best practice recommendations for Zig code Integrate Zig tooling into AI-assisted development workflows

README

Zig MCP Server

A Model Context Protocol (MCP) server that provides Zig language tooling, code analysis, and documentation access. This server enhances AI capabilities with Zig-specific functionality including code optimization, compute unit estimation, code generation, and best practices recommendations.

Features

Tools

1. Code Optimization (optimize_code)

Analyzes and optimizes Zig code with support for different optimization levels:

  • Debug
  • ReleaseSafe
  • ReleaseFast
  • ReleaseSmall
// 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

  1. Clone the repository:
git clone [repository-url]
cd zig-mcp-server
  1. Install dependencies:
npm install
  1. Build the server:
npm run build
  1. 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
  1. 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(u8, 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.

zig-mcp-server FAQ

How does the zig-mcp-server optimize Zig code?
It analyzes code and applies optimizations based on selected levels like Debug, ReleaseSafe, ReleaseFast, and ReleaseSmall.
Can the server estimate resource usage of Zig programs?
Yes, it estimates memory usage, time complexity, and allocation patterns to help understand computational costs.
What kind of code generation does the server support?
It generates Zig code snippets from user inputs or specifications to accelerate development.
Is the zig-mcp-server suitable for integrating with AI models?
Yes, it enhances AI capabilities by providing Zig-specific code analysis and generation tools.
Does the server support multiple optimization levels?
Yes, it supports Debug, ReleaseSafe, ReleaseFast, and ReleaseSmall optimization levels.
How can I use the compute units estimation feature?
Provide Zig code to the server, and it returns detailed analysis of memory and time complexity.
Is the zig-mcp-server open source?
The details are not specified here; check the official repository for licensing and source code.
Can this server help improve Zig code quality?
Yes, by recommending best practices and optimizing code, it helps improve overall code quality.