Unichat MCP Server

Unichat MCP Server

Universal MCP server providing context-aware AI chat and code tools across major model vendors.

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Unichat MCP Server enables sending standardized requests to leading AI model vendors, including OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, and Inception, utilizing the Model Context Protocol. It features unified endpoints for chat interactions and provides specialized tools for code review, documentation generation, code explanation, and programmatic code reworking. The server is designed for seamless integration with platforms like Claude Desktop and installation via Smithery. Vendor API keys are required for secure access to supported providers.

Key Features

MCP protocol compliance for AI model requests
Unified interface for multi-vendor model access
Context-supported chat tool
Automated code review tool
Code documentation generation
Code explanation and walkthroughs
Code reworking and refactoring via prompts
Integration with Claude Desktop
Easy deployment via Smithery
Vendor API key support for secure model access

Use Cases

Automated code best practices review
Generating detailed explanations of code functionality
Creating or improving inline documentation and docstrings
Applying code changes programmatically based on prompt instructions
Building developer productivity tools for chat and code management
Integrating AI-powered code review into CI/CD pipelines
Providing standardized AI chat interfaces in software products
Connecting a single toolchain to multiple AI model providers
Rapid prototyping of AI-driven language features
Enhancing software development environments with contextual AI assistance

README

Unichat MCP Server in Python

Also available in TypeScript

Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, Inception using MCP protocol via tool or predefined prompts. Vendor API key required

Tools

The server implements one tool:

  • unichat: Send a request to unichat
    • Takes "messages" as required string arguments
    • Returns a response

Prompts

  • code_review
    • Review code for best practices, potential issues, and improvements
    • Arguments:
      • code (string, required): The code to review"
  • document_code
    • Generate documentation for code including docstrings and comments
    • Arguments:
      • code (string, required): The code to comment"
  • explain_code
    • Explain how a piece of code works in detail
    • Arguments:
      • code (string, required): The code to explain"
  • code_rework
    • Apply requested changes to the provided code
    • Arguments:
      • changes (string, optional): The changes to apply"
      • code (string, required): The code to rework"

Quickstart

Install

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

Supported Models:

A list of currently supported models to be used as "SELECTED_UNICHAT_MODEL" may be found here. Please make sure to add the relevant vendor API key as "YOUR_UNICHAT_API_KEY"

Example:

json
"env": {
  "UNICHAT_MODEL": "gpt-4o-mini",
  "UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}

Development/Unpublished Servers Configuration

json
"mcpServers": {
  "unichat-mcp-server": {
    "command": "uv",
    "args": [
      "--directory",
      "{{your source code local directory}}/unichat-mcp-server",
      "run",
      "unichat-mcp-server"
    ],
    "env": {
      "UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
      "UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
    }
  }
}

Published Servers Configuration

json
"mcpServers": {
  "unichat-mcp-server": {
    "command": "uvx",
    "args": [
      "unichat-mcp-server"
    ],
    "env": {
      "UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
      "UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
    }
  }
}

Installing via Smithery

To install Unichat for Claude Desktop automatically via Smithery:

bash
npx -y @smithery/cli install unichat-mcp-server --client claude

Development

Building and Publishing

To prepare the package for distribution:

  1. Remove older builds:
bash
rm -rf dist
  1. Sync dependencies and update lockfile:
bash
uv sync
  1. Build package distributions:
bash
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
bash
uv publish --token {{YOUR_PYPI_API_TOKEN}}

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

bash
npx @modelcontextprotocol/inspector uv --directory {{your source code local directory}}/unichat-mcp-server run unichat-mcp-server

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

Star History

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Repository Details

Language Python
Default Branch main
Size 226 KB
Contributors 4
License MIT License
MCP Verified Nov 12, 2025

Programming Languages

Python
93.77%
Dockerfile
6.23%

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