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 The server implements one tool: - unichat: Send a request to unichat - Takes "messages" as required string arguments - Returns a response - codereview - Review code for best practices, potential issues, a
Add this skill
npx mdskills install amidabuddha/unichat-mcp-serverEnables multi-vendor LLM access with useful code-focused prompts, but permissions are overly broad




Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, Inception using MCP protocol via tool or predefined prompts. Vendor API key required
The server implements one tool:
unichat: Send a request to unichat
code_review
code (string, required): The code to review"document_code
code (string, required): The code to comment"explain_code
code (string, required): The code to explain"code_rework
changes (string, optional): The changes to apply"code (string, required): The code to rework"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Development/Unpublished Servers Configuration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"
}
}
}
To install Unichat for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install unichat-mcp-server --client claude
To prepare the package for distribution:
rm -rf dist
uv sync
uv build
This will create source and wheel distributions in the dist/ directory.
uv publish --token {{YOUR_PYPI_API_TOKEN}}
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.
Install via CLI
npx mdskills install amidabuddha/unichat-mcp-serverUnichat MCP Server in Python is a free, open-source AI agent skill. 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 The server implements one tool: - unichat: Send a request to unichat - Takes "messages" as required string arguments - Returns a response - codereview - Review code for best practices, potential issues, a
Install Unichat MCP Server in Python with a single command:
npx mdskills install amidabuddha/unichat-mcp-serverThis downloads the skill files into your project and your AI agent picks them up automatically.
Unichat MCP Server in Python works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Gemini Cli, Amp, Roo Code, Goose. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.