Vox MCP

Multi-model AI gateway for MCP clients.

Why

MCP clients like Claude Code, Claude Desktop, and Cursor are locked to their host model. Vox gives them access to every other model — Gemini, GPT, Grok, DeepSeek, Kimi, or your local Ollama — through a single chat tool.

The design is deliberately minimal: prompts go to providers unmodified, responses come back unmodified. No system prompt injection. No response formatting. No behavioral directives. The only value Vox adds is routing and conversation memory — everything else is pure passthrough.

What it does

Send a prompt, optionally attach files or images, pick a model (or let the agent pick), and get back the model's raw response. Conversation threads persist in memory via continuation_id for multi-turn exchanges across any provider — start a thread with Gemini, continue it with GPT. Threads are shadow-persisted to disk as JSONL for durability and can be exported as Markdown.

3 tools:

8 providers:

Quick start

git clone https://github.com/linxule/vox-mcp.git
cd vox-mcp
cp .env.example .env
# Edit .env — add at least one API key
uv sync
uv run python server.py

MCP client configuration

Vox runs as a stdio MCP server. Each client needs to know how to launch it.

Replace /path/to/vox-mcp with the absolute path to your cloned repo.

Claude Code (CLI)

claude mcp add vox-mcp \
  -e GEMINI_API_KEY=your-key-here \
  -- uv run --directory /path/to/vox-mcp python server.py

Or add to .mcp.json in your project root:

{
  "mcpServers": {
    "vox-mcp": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/vox-mcp", "python", "server.py"],
      "env": {
        "GEMINI_API_KEY": "your-key-here"
      }
    }
  }
}

Claude Desktop

Add to claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "vox-mcp": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/vox-mcp", "python", "server.py"],
      "env": {
        "GEMINI_API_KEY": "your-key-here"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{
  "mcpServers": {
    "vox-mcp": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/vox-mcp", "python", "server.py"],
      "env": {
        "GEMINI_API_KEY": "your-key-here"
      }
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "vox-mcp": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/vox-mcp", "python", "server.py"],
      "env": {
        "GEMINI_API_KEY": "your-key-here"
      }
    }
  }
}

Any MCP client

The canonical stdio configuration:

{
  "mcpServers": {
    "vox-mcp": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/vox-mcp", "python", "server.py"],
      "env": {
        "GEMINI_API_KEY": "your-key-here"
      }
    }
  }
}

Tips:

• Paths must be absolute
• You only need one API key to start — add more providers later via .env
• The .env file in the vox-mcp directory is loaded automatically, so API keys can go there instead of in the client config
• Use VOX_FORCE_ENV_OVERRIDE=true in .env if client-passed env vars conflict with your .env values

Configuration

Copy .env.example to .env and configure:

• API keys — at least one provider key is required
• DEFAULT_MODEL — auto (default, agent picks) or a specific model name
• Model restrictions — GOOGLE_ALLOWED_MODELS, OPENAI_ALLOWED_MODELS, etc.
• CONVERSATION_TIMEOUT_HOURS — thread TTL (default: 24h)
• MAX_CONVERSATION_TURNS — thread length limit (default: 100)

See .env.example for the full reference.

Development

uv sync
uv run python -c "import server"   # smoke test
uv run pytest                       # run tests

See CONTRIBUTING.md for code style, project structure, and how to add providers.

License

Apache 2.0 — see LICENSE and NOTICE.

Derived from pal-mcp-server by Beehive Innovations.