Model Runner

Model Runner

Provides a unified MCP interface for running completions, embeddings, image generation, and classification across OpenAI, Anthropic, Groq, and Mistral. Eliminates provider-specific boilerplate by standardizing API calls for text generation, vector embeddings, and classification tasks.

Category
Visit Server

README

Model Runner

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

MCPize License: MIT

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

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

Tool What it does
list_supported_models Browse the full catalog of models by provider and capability
run_completion Text generation via OpenAI, Anthropic, Groq, or Mistral
run_embedding Vector embeddings via OpenAI or Cohere
run_image_generation Image generation via DALL-E 2 or DALL-E 3
estimate_tokens Estimate token count before making expensive API calls
run_classification Zero-shot text classification with confidence scores

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

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured