Which LLM providers are supported?
OpenAI (GPT models), Anthropic (Claude models), Google (Gemini models), and DeepSeek.
@sjquant
Basic information
A model-agnostic Message Control Protocol (MCP) server that enables seamless integration with various Large Language Models (LLMs) like GPT, DeepSeek, Claude, and more.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"llm-bridge-mcp": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@sjquant/llm-bridge-mcp",
"--client",
"claude"
]
}
}
}The text prompt to send to the LLM
Specific model to use (default: "openai:gpt-4o-mini")
Controls randomness (0.0 to 1.0)
Maximum number of tokens to generate
Optional system prompt to guide the model's behavior
LLM Bridge MCP allows AI agents to interact with multiple large language models through a standardized interface. It leverages the Message Control Protocol (MCP) to provide seamless access to different LLM providers, making it easy to switch between models or use multiple models in the same application.
Configure API keys in a .env file (or pass them as environment variables) and then add a server entry to your Claude Desktop or Cursor configuration. The server exposes a single tool, run_llm, which accepts a prompt, optional model name (default openai:gpt-4o-mini), temperature, max tokens, and system prompt.
run_llm.OpenAI (GPT models), Anthropic (Claude models), Google (Gemini models), and DeepSeek.
You can install it automatically via Smithery (`npx -y @smithery/cli install @sjquant/llm-bridge-mcp --client claude`) or manually by cloning the repository and following the manual installation steps.
Create a `.env` file in the root directory with keys like `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `GOOGLE_API_KEY`, and `DEEPSEEK_API_KEY`. Alternatively, pass them as environment variables in the MCP server configuration.
Add a server entry to your Claude Desktop configuration or `.cursor/mcp.json` file, specifying the command `uvx` and the package name `llm-bridge-mcp`, along with the required API keys.
It means the system cannot find the `uvx` executable in your PATH. Find the full path to `uvx` using `which uvx` (macOS/Linux) or `where.exe uvx` (Windows), then update your MCP server configuration to use that full path.

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