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Zig MCP Server

by openSVM
OverviewInspectNewSchemaRelated ServersScore
TypeScript
Remote
MIT License
34

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.

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

How are these scores calculated?

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