Model Runner

Stop copy-pasting boilerplate every time you need to call a different AI model.

Model Runner is an MCP server that gives any AI assistant a unified interface to run completions, embeddings, image generation, and classification across all major providers. One tool call instead of per-provider API clients.

Quick Start

Add to your mcpServers config:

{
  "mcpServers": {
    "model-runner": {
      "url": "https://your-cloud-run-url/mcp"
    }
  }
}

Or run locally:

npm install
npm start

Related MCP server: Multi-Provider LLM MCP Server

Before / After

Before: Your assistant wants to classify customer feedback into sentiment buckets. It cannot call the OpenAI API natively, does not know the exact endpoint shape, and cannot handle auth headers.

// 30 lines of fetch boilerplate. Per provider. Per project.
// Auth headers, message array format, error shapes, all different.

After: One tool call:

{
  "tool": "run_classification",
  "arguments": {
    "text": "Waited 40 minutes for support and got no answer",
    "labels": ["positive", "negative", "neutral"],
    "api_key": "sk-..."
  }
}

Output:

{
  "label": "negative",
  "confidence": 0.97,
  "reasoning": "The customer experienced a long wait with no resolution, indicating a clearly negative experience."
}

Tools

Who is this for?

• AI assistant builders who want their agent to invoke ML models without hardcoding provider-specific API logic into every project

• Developers prototyping who need a quick way to compare outputs across OpenAI, Anthropic, Groq, and Mistral without writing multiple API clients

• Data teams running pipelines who want a single MCP endpoint to classify, embed, or summarize records at scale without managing provider SDKs

Health Check

Both endpoints return the same response and require no authentication:

GET /
GET /health

Response:

{
  "status": "ok",
  "server": "model-runner",
  "version": "1.0.0",
  "tools": 6
}

Built by

Mastermind HQ - AI tools built for builders.

License

MIT