# Unichat Mcp Server

> MCP server from amidabuddha/unichat-mcp-server.

- **Type:** MCP server
- **Install:** `agentstack add mcp-amidabuddha-unichat-mcp-server`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [amidabuddha](https://agentstack.voostack.com/s/amidabuddha)
- **Installs:** 0
- **Category:** [Integrations](https://agentstack.voostack.com/c/integrations)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [amidabuddha](https://github.com/amidabuddha)
- **Source:** https://github.com/amidabuddha/unichat-mcp-server

## Install

```sh
agentstack add mcp-amidabuddha-unichat-mcp-server
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Unichat MCP Server in Python
Also available in [TypeScript](https://github.com/amidabuddha/unichat-ts-mcp-server)
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Send requests to OpenAI, Anthropic, and OpenAI-compatible providers using MCP protocol via tool or predefined prompts. For OpenAI-compatible providers such as MistralAI, xAI, Google AI, DeepSeek, Alibaba, or Inception, set `UNICHAT_BASE_URL` to the provider's compatible API endpoint.
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 make sure to add the relevant vendor API key as `"YOUR_UNICHAT_API_KEY"`

**Example:**
```json
"env": {
  "UNICHAT_MODEL": "gpt-5.4-mini",
  "UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}
```

For OpenAI-compatible providers with custom endpoints:
```json
"env": {
  "UNICHAT_MODEL": "PROVIDER_MODEL",
  "UNICHAT_API_KEY": "YOUR_PROVIDER_API_KEY",
  "UNICHAT_BASE_URL": "https://provider.example.com/v1"
}
```

When `UNICHAT_BASE_URL` is set, the server accepts the configured `UNICHAT_MODEL` without checking it against Unichat's built-in model list.

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. Remove older builds:
```bash
rm -rf dist
```

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

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

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

4. 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.

## Hosted deployment

A hosted deployment is available on [Fronteir AI](https://fronteir.ai/mcp/amidabuddha-unichat-mcp-server).

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [amidabuddha](https://github.com/amidabuddha)
- **Source:** [amidabuddha/unichat-mcp-server](https://github.com/amidabuddha/unichat-mcp-server)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-amidabuddha-unichat-mcp-server
- Seller: https://agentstack.voostack.com/s/amidabuddha
- Browse the marketplace: https://agentstack.voostack.com/browse

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