# Replicate MCP Server

> Official remote Model Context Protocol server for Replicate's AI models API. Enables creating, tracking, and canceling model predictions, searching models and collections, with automatic API deployment on GPU clusters and production-grade control.

- **URL:** https://mcp.replicate.com/
- **Category:** AI Integration MCP Servers
- **Tags:** Model Deployment, Inference, Gpu
- **Featured:** yes
- **Updated:** 2026-03-20 19:40
- **Canonical page:** https://mcpserver.ever.works/items/replicate-mcp-server

## Details

## Overview

The Model Context Protocol (MCP) is an open standard developed by Anthropic that defines how applications share context with large language models (LLMs). Replicate's MCP server extends the capabilities of apps like Claude Desktop, Claude Code, Cursor, or GitHub Copilot by feeding them OpenAPI schemas that describe Replicate's HTTP API.

## Key Features

The server empowers users to run Replicate models through a tool-based interface, offering:

- **Model Search**: Search and browse Replicate models and collections
- **Prediction Management**: Create, track, and cancel Replicate model predictions
- **Status Tracking**: Monitor prediction progress in real-time
- **Image Management**: Handle image inputs and outputs
- **Model Information**: Access detailed model metadata and documentation

## Installation Options

### Remote Server (Recommended)

The easiest option for most users:
- Hosted server automatically updated with latest features
- Just add the hosted server URL to apps like Claude or Cursor
- No local installation required
- Visit mcp.replicate.com to get started

### Local Server

Run the server locally on your machine:
- Install server locally
- Configure in your AI apps
- Full control over server environment
- GitHub: deepfates/mcp-replicate

## API Deployment

When you push a model to Replicate:
- Automatic API server generation
- Deployment on Replicate's GPU cluster
- Production-grade infrastructure

### Production Deployments

For production use, create a deployment to get:
- Full control over scaling
- Hardware selection (GPU types)
- Performance optimization
- Private, dedicated API endpoint
- Production-grade control over infrastructure

## Security Features

Cloudflare's OAuth Provider Framework for Workers:
- Keeps Replicate API token secure
- OAuth authentication flow
- Secure token management
- Enterprise-grade security

## Use Cases

- Running AI models from chat interfaces
- Automated prediction workflows
- Model discovery and exploration
- Image generation and processing
- Multi-model orchestration
- Production AI deployment
- Research and experimentation

## Compatible Clients

- Claude Desktop and Claude Code
- Cursor IDE
- GitHub Copilot
- VS Code extensions
- Any MCP-compatible AI assistant

## Model Capabilities

Access to thousands of AI models:
- Image generation (Stable Diffusion, DALL-E variants)
- Language models (Llama, Mistral, etc.)
- Image processing and upscaling
- Video generation
- Audio synthesis
- Custom models

## Technical Features

- RESTful API integration
- WebSocket support for streaming
- Batch prediction capabilities
- Custom model deployment
- GPU cluster management
- Automatic scaling

## Developer Experience

- OpenAPI schema integration
- Tool-based interface
- Natural language model interaction
- Automatic prediction tracking
- Status monitoring
- Error handling

## Pricing

Pay-per-use pricing:
- Charged by compute time
- Different rates for different GPU types
- Free tier available for testing
- Production deployment pricing
- Custom enterprise pricing available

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