
Unichat
Sends chat requests to multiple LLM APIs (OpenAI, Anthropic, Google, etc.) through a single unified interface. Includes built-in prompts for code review, documentation, and explanation tasks.
Interact with multiple LLM chat APIs through a unified interface.
What it does
- Send messages to 8+ LLM providers via one interface
- Review code for best practices and issues
- Generate code documentation and comments
- Explain code functionality in detail
- Apply requested changes to code
Best for
About Unichat
Unichat is a community-built MCP server published by amidabuddha that provides AI assistants with tools and capabilities via the Model Context Protocol. Unichat lets you interact with multiple LLM chat APIs easily through a unified interface. Simplify your workflows with U It is categorized under ai ml, developer tools.
How to install
You can install Unichat in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
Unichat is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
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:
"env": {
"UNICHAT_MODEL": "gpt-4o-mini",
"UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}
Development/Unpublished Servers Configuration
"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
"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:
npx -y @smithery/cli install unichat-mcp-server --client claude
Development
Building and Publishing
To prepare the package for distribution:
- Remove older builds:
rm -rf dist
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- 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.
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