What is Unichat Mcp Server

unichat-mcp-server is a Python-based server that facilitates communication with various AI models, including OpenAI, MistralAI, Anthropic, xAI, Google AI, and DeepSeek using the MCP protocol.

Use cases

Use cases include reviewing code for best practices, generating documentation for existing code, explaining complex code snippets, and making requested changes to code.

How to use

To use unichat-mcp-server, install it and configure your environment with the required vendor API key. You can send requests using the ‘unichat’ tool with specific prompts for tasks like code review, documentation generation, and code explanation.

Key features

Key features include the ability to send requests to multiple AI vendors, support for various prompts (code review, document generation, code explanation, and code rework), and a straightforward installation process.

Where to use

unichat-mcp-server can be used in software development environments, educational settings for learning programming, and any application requiring AI-assisted coding tasks.

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:

Development/Unpublished Servers Configuration

Published Servers Configuration

Installing via Smithery

To install Unichat for Claude Desktop automatically via Smithery:

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

Development

Building and Publishing

To prepare the package for distribution:

1. Remove older builds:

rm -rf dist

2. Sync dependencies and update lockfile:

uv sync

3. Build package distributions:

uv build

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

4. Publish to PyPI:

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:

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.