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Zig MCP Server

by openSVM
GitHub
JavaScript
MIT License
27
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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.

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Tools

Provides Zig language tooling and code analysis, enhancing AI capabilities with Zig-specific functions like code optimization, compute unit estimation, code generation, and recommendations for best practices.

  1. Features
    1. Tools
    2. Resources
  2. Installation
    1. Usage Examples
      1. 1. Optimize Code
      2. 2. Estimate Compute Units
      3. 3. Generate Code
      4. 4. Get Recommendations
    2. Development
      1. Project Structure
      2. Building
      3. Testing
    3. Contributing
      1. License

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