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Runware MCP Server

A powerful Model Context Protocol (MCP) server that provides lightning fast image and video generation tools using the Runware API. This server supports both SSE (Server-Sent Events) transport for custom claude connector and direct claude desktop installation as well.

Features

Image Generation Tools

  • imageInference: Full-featured image generation with advanced parameters

  • photoMaker: Subject personalization with PhotoMaker technology

  • imageUpscale: High-quality image resolution enhancement

  • imageBackgroundRemoval: Background removal with multiple AI models

  • imageCaption: AI-powered image description generation

  • imageMasking: Automatic mask generation for faces, hands, and people

Video Generation Tools

  • videoInference: Text-to-video and image-to-video generation

  • listVideoModels: Discover available video models

  • getVideoModelInfo: Get detailed model specifications

Utility Tools

  • imageUpload: Upload local images to get Runware UUIDs

  • modelSearch: Search and discover AI models on the platform

Smart Features

  • Automatic Model Selection: I2V uses klingai:5@2, T2V uses google:3@1

  • Input Validation: Prevents Claude upload URL pasting and validates dimensions

  • Comprehensive Error Handling: Clear error messages and guidance

Demo

Watch the demo video to see the Runware MCP server in action:

https://github.com/user-attachments/assets/9732096b-8513-455c-9759-cc88363c42f9

Architecture

[ MCP Client / AI Assistant ] | (connects via SSE over HTTP) | [ Uvicorn Server ] | [ Starlette App ] | [ FastMCP Server ] | [ Runware API ]

Prerequisites

  • Python: 3.10 or higher

  • Runware API Key: Get your API key from Runware Dashboard

  • Dependencies: See requirements.txt or pyproject.toml

Installation

1. Clone the Repository

git clone https://github.com/Runware/MCP-Runware.git cd MCP-Runware

2. Install Dependencies

# Using uv (recommended) uv venv source .venv/bin/activate uv pip install . # Or using pip pip install -r requirements.txt

3. Environment Setup

Create a .env file in the project root:

RUNWARE_API_KEY=your_api_key_here

Deployment Methods

Method 1: SSE Server (Recommended for Production)

Docker Deployment

# Build the Docker image docker build -t runware_mcp_sse . # Run the container docker run --rm -p 8081:8081 runware_mcp_sse

Method 2: MCP Install (Direct Integration)

Install in Claude Desktop

# From the project directory mcp install --with-editable . runware_mcp_server.py

Model Recommendations

Image Generation

  • Default: civitai:943001@1055701 (SDXL-based)

  • PhotoMaker: civitai:139562@344487 (RealVisXL V4.0)

  • Background Removal: runware:109@1 (RemBG 1.4)

Video Generation

  • Image-to-Video (I2V): klingai:5@2 (1920x1080)

  • Text-to-Video (T2V): google:3@1 (1280x720)

You can find all additional models here: Runware Models

Configuration

Environment Variables

  • RUNWARE_API_KEY: Your Runware API key (required)

Input Validation

  • Rejects Claude upload URLs (https://files.*). Claude tends to include base64 strings in its reasoning/thinking process, which rapidly fills the context window with garbage data. Learn more about this issue

  • Supports local file paths, public accessible URLs (make sure it has proper file extension such as JPG, PNG, WEBP, etc), and Runware UUIDs

Support

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security - not tested
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license - not found
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quality - not tested

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