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Zig MCP Server

by MCP-Mirror

Development/Language ToolsZigLanguage ServerCode AnalysisCode Generation

The Zig MCP Server provides Zig language tooling, code analysis, and documentation access. It enhances AI capabilities with Zig-specific functionality including code optimization and code generation.

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What is Zig MCP Server?

A Model Context Protocol (MCP) server that provides Zig language tooling, code analysis, and documentation access. It's designed to enhance AI capabilities by offering Zig-specific functionalities.

How to use Zig MCP Server?

  1. Clone the repository. 2. Install dependencies using npm install. 3. Build the server using npm run build. 4. Configure environment variables, especially the GITHUB_TOKEN. 5. Add the server to your MCP settings with the provided configuration.

Key features of Zig MCP Server

  • Code Optimization

  • Compute Units Estimation

  • Code Generation from natural language

  • Code Recommendations and best practices

  • Access to Zig Language Reference

  • Access to Standard Library Documentation

  • Access to Popular Zig Repositories

Use cases of Zig MCP Server

  • Optimizing Zig code for performance or size

  • Estimating the computational complexity of Zig code

  • Generating Zig code from natural language descriptions

  • Getting recommendations for improving Zig code

  • Accessing Zig language documentation

  • Learning from community examples and patterns

  • Integrating Zig tooling into AI workflows

FAQ from Zig MCP Server

What is MCP?

MCP stands for Model Context Protocol. It's a protocol that allows different tools and services to communicate and share context.

Why do I need a GitHub token?

A GitHub token is needed to increase the API rate limits when accessing resources from GitHub, such as popular repositories.

What optimization levels are supported?

The code optimization tool supports Debug, ReleaseSafe, ReleaseFast, and ReleaseSmall optimization levels.

Can I generate code for specific tasks?

Yes, the code generation tool allows you to generate Zig code from natural language prompts with optional context.

How can I contribute to this project?

Fork the repository, create a feature branch, commit your changes, push to the branch, and open a pull request.