An open API service indexing awesome lists of open source software.

https://github.com/MCP-Mirror/amidabuddha_unichat-mcp-server

Mirror of https://github.com/amidabuddha/unichat-mcp-server
https://github.com/MCP-Mirror/amidabuddha_unichat-mcp-server

Last synced: 2 months ago
JSON representation

Mirror of https://github.com/amidabuddha/unichat-mcp-server

Awesome Lists containing this project

README

          

# Unichat MCP Server in Python
Also available in [TypeScript](https://github.com/amidabuddha/unichat-ts-mcp-server)
--



Released under the MIT license.


Smithery Server Installations

Send requests to OpenAI, MistralAI, Anthropic, xAI, or Google AI 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](https://github.com/amidabuddha/unichat/blob/main/unichat/models.py). Please makes 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Development/Unpublished Servers Configuration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](https://smithery.ai/server/unichat-mcp-server):

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

## Development

### Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:
```bash
uv sync
```

2. Build package distributions:
```bash
uv build
```

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

3. 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](https://github.com/modelcontextprotocol/inspector).

You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-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.