mcp.zig
Health Gecti
- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 23 GitHub stars
Code Uyari
- network request — Outbound network request in docs/package-lock.json
Permissions Gecti
- Permissions — No dangerous permissions requested
This tool provides a comprehensive Model Context Protocol (MCP) library designed to bring MCP support directly to the Zig programming ecosystem. It acts as a bridge to connect AI applications with external systems.
Security Assessment
Overall Risk: Low. The tool does not request any dangerous system permissions or execute hidden shell commands. There are no hardcoded secrets detected within the codebase. A standard automated scan flagged an outbound network request, but this originates from a documentation configuration file (`docs/package-lock.json`) used for building the project's website, meaning the core library itself is safe from malicious network activity.
Quality Assessment
The project demonstrates strong health and maintenance signals. It is licensed under the standard MIT license, allowing for broad commercial and private use with minimal restrictions. Activity is highly recent, with the latest repository pushes occurring just today. Community trust is currently in its early stages but remains positive, backed by 23 GitHub stars. Furthermore, the repository features robust automated CI/CD pipelines, documentation deployments, and good platform support (Linux, Windows, macOS), indicating a professional and reliable project structure.
Verdict
Safe to use.
A comprehensive Model Context Protocol (MCP) library for Zig — bringing MCP support to the Zig ecosystem.
MCP.zig
A Model Context Protocol (MCP) library for the Zig ecosystem.
🔌 What is MCP?
Model Context Protocol (MCP) is an open-source standard for connecting AI applications to external systems.
Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect electronic devices, MCP provides a standardized way to connect AI applications to external systems.
🎯 Why mcp.zig?
The Model Context Protocol (MCP) is an open standard by Anthropic for connecting AI applications to external systems. While MCP has official SDKs for TypeScript, Python, and other languages, Zig currently lacks proper MCP support.
mcp.zig aims to fill this gap by providing a native, high-performance MCP implementation for the Zig programming language, enabling Zig developers to:
- 🔧 Build MCP servers that expose tools, resources, and prompts to AI applications
- 🔌 Create MCP clients that connect to any MCP-compatible server
- ⚡ Leverage Zig's performance and safety features for AI integrations
✨ Features
- 🛠️ Server Framework - Build MCP servers that expose tools, resources, and prompts
- 🔌 Client Framework - Create MCP clients with full support for roots, sampling, and elicitation
- 🚀 Tasks System - Advanced support for long-running, interactive tasks
- 📦 Rich Content - Full support for text, images, audio, and embedded resources
- 📡 Transport Layer - STDIO and HTTP transport support
- 📋 Full Protocol Support - JSON-RPC 2.0, capability negotiation, lifecycle management
- ⚡ Native Performance - Written in pure Zig for optimal performance
- 🧪 Comprehensive Testing - Unit tests for all components
📚 Documentation
Full documentation is available at muhammad-fiaz.github.io/mcp.zig
For the official MCP specification and resources, visit:
🚀 Quick Start
Installation
Run the following command to add mcp.zig to your project:
# Latest development branch
zig fetch --save git+https://github.com/muhammad-fiaz/mcp.zig.git
# Or specific release
zig fetch --save https://github.com/muhammad-fiaz/mcp.zig/archive/refs/tags/0.0.3.tar.gz
Then in your build.zig:
const mcp_dep = b.dependency("mcp", .{
.target = target,
.optimize = optimize,
});
exe.root_module.addImport("mcp", mcp_dep.module("mcp"));
Creating a Server
const std = @import("std");
const mcp = @import("mcp");
pub fn main() void {
if (run()) {} else |err| {
mcp.reportError(err);
}
}
fn run() !void {
var gpa = std.heap.GeneralPurposeAllocator(.{}){};
defer _ = gpa.deinit();
const allocator = gpa.allocator();
// Check for updates
_ = mcp.report.checkForUpdates(allocator);
// Create server
var server = mcp.Server.init(.{
.name = "my-server",
.version = "1.0.0",
.allocator = allocator,
});
defer server.deinit();
// Enable tools capability
server.enableTools();
// Add a tool
try server.addTool(.{
.name = "greet",
.description = "Greet a user",
.handler = greetHandler,
});
// Run with STDIO transport
try server.run(.stdio);
}
fn greetHandler(
allocator: std.mem.Allocator,
args: ?std.json.Value
) mcp.tools.ToolError!mcp.tools.ToolResult {
const name = mcp.tools.getString(args, "name") orelse "World";
const message = try std.fmt.allocPrint(allocator, "Hello, {s}!", .{name});
return mcp.tools.textResult(allocator, message);
}
Creating a Client
const std = @import("std");
const mcp = @import("mcp");
pub fn main() void {
if (run()) {} else |err| {
mcp.reportError(err);
}
}
fn run() !void {
var gpa = std.heap.GeneralPurposeAllocator(.{}){};
defer _ = gpa.deinit();
const allocator = gpa.allocator();
var client = mcp.Client.init(.{
.name = "my-client",
.version = "1.0.0",
.allocator = allocator,
});
defer client.deinit();
// Enable capabilities
client.enableSampling();
client.enableRoots(true); // Supports list changed notifications
// Add roots
try client.addRoot("file:///projects", "Projects");
}
📁 Examples
The examples/ directory contains several example implementations:
| Example | Description |
|---|---|
| simple_server.zig | Basic server with greeting tool |
| simple_client.zig | Basic client setup |
| weather_server.zig | Weather information server |
| calculator_server.zig | Calculator with arithmetic operations |
Run examples:
# Build all examples
zig build
# Run examples
zig build run-server
zig build run-weather
zig build run-calc
🏗️ Architecture
src/
├── mcp.zig # Main entry point
├── protocol/
│ ├── protocol.zig # MCP protocol definitions
│ ├── types.zig # Type definitions
│ ├── jsonrpc.zig # JSON-RPC 2.0 implementation
│ └── schema.zig # JSON Schema utilities
├── transport/
│ └── transport.zig # STDIO and HTTP transports
├── server/
│ ├── server.zig # Server implementation
│ ├── tools.zig # Tool primitive
│ ├── resources.zig # Resource primitive
│ └── prompts.zig # Prompt primitive
└── client/
└── client.zig # Client implementation
🛠️ Server Features
Tools
Tools are executable functions that AI applications can invoke:
try server.addTool(.{
.name = "search_files",
.description = "Search for files matching a pattern",
.handler = searchHandler,
});
Resources
Resources provide read-only data to AI applications:
try server.addResource(.{
.uri = "file:///docs/readme.md",
.name = "README",
.mimeType = "text/markdown",
.handler = readFileHandler,
});
Prompts
Prompts are reusable templates for LLM interactions:
try server.addPrompt(.{
.name = "summarize",
.description = "Summarize a document",
.arguments = &.{
.{ .name = "document", .required = true },
},
.handler = summarizeHandler,
});
🔌 Client Features
Roots
Define filesystem boundaries:
client.enableRoots(true);
try client.addRoot("file:///projects", "Projects");
Sampling
Allow servers to request LLM completions:
client.enableSampling();
🧪 Testing
Run the test suite:
zig build test
Compile tests for a target without executing them (useful for cross-target validation):
zig build test-compile -Dtarget=x86_64-linux
zig build test-compile -Dtarget=x86_64-windows
zig build test-compile -Dtarget=x86_64-macos
📖 Protocol Version
This library implements MCP protocol version 2025-11-25.
| Version | Status |
|---|---|
| 2025-11-25 | ✅ Supported |
| 2025-06-18 | ✅ Compatible |
| 2025-03-26 | ✅ Compatible |
| 2024-11-05 | ✅ Compatible |
🤝 Contributing
Contributions are welcome! Please feel free to submit issues and pull requests.
See Contributing Guide for guidelines.
💖 Support
If you find this project helpful, consider supporting its development:
📄 License
MIT License - see LICENSE for details.
🔗 Resources
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