run_llm(
    prompt: str,
    model_name: KnownModelName = "openai:gpt-4o-mini",
    temperature: float = 0.7,
    max_tokens: int = 8192,
    system_prompt: str = "",
) -> LLMResponse

npx -y @smithery/cli install @sjquant/llm-bridge-mcp --client claude

git clone https://github.com/yourusername/llm-bridge-mcp.git
cd llm-bridge-mcp

# On macOS
brew install uv

# On Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
GOOGLE_API_KEY=your_google_api_key
DEEPSEEK_API_KEY=your_deepseek_api_key

"mcpServers": {
  "llm-bridge": {
    "command": "uvx",
    "args": [
      "llm-bridge-mcp"
    ],
    "env": {
      "OPENAI_API_KEY": "your_openai_api_key",
      "ANTHROPIC_API_KEY": "your_anthropic_api_key",
      "GOOGLE_API_KEY": "your_google_api_key",
      "DEEPSEEK_API_KEY": "your_deepseek_api_key"
    }
  }
}

# On macOS/Linux
which uvx

# On Windows
where.exe uvx

"mcpServers": {
  "llm-bridge": {
    "command": "/full/path/to/uvx",  // Replace with your actual path
    "args": [
      "llm-bridge-mcp"
    ],
    "env": {
      // ... your environment variables
    }
  }
}