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MCP Server for Replicate

@MCP-Mirror

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

MCP-Mirror

关于 MCP Server for Replicate

Mirror of

#mcp#replicate#ai-models

MCP Server for Replicate 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

MCP Server for Replicate 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Server for Replicate?

MCP Server for Replicate is a FastMCP server that provides a standardized interface for accessing AI models hosted on Replicate’s API. It currently focuses on image generation, including model schema inspection, customizable parameters, and output resizing/optimization. This server is for developers who want to integrate Replicate models into MCP-compatible tools.

How to use MCP Server for Replicate?

Install dependencies with pip install -r requirements.txt, set your Replicate API token in a .env file as REPLICATE_API_TOKEN=your_token_here, then run the server using fastmcp dev.

Key features of MCP Server for Replicate

  • Image generation with customizable parameters
  • Model schema inspection for supported models
  • Output resizing and optimization
  • Early alpha stage with active development
  • Roadmap includes text and video generation support

Use cases of MCP Server for Replicate

  • Generating images from text prompts using Replicate-hosted models
  • Inspecting the input/output schemas of available image models
  • Integrating Replicate’s AI capabilities into MCP-enabled workflows

常见问题

1

What models are currently supported?

Image generation models are supported, with features for schema inspection, generation with parameters, and output optimization.

2

How do I set up my API token?

Add `REPLICATE_API_TOKEN=your_token_here` to a `.env` file in the project directory.

3

What is the current status of the server?

It is in early alpha development; features and APIs may change significantly.

4

What are the planned future features?

The roadmap includes text generation, video generation, model version management, better error handling, caching, and rate limiting.

5

How do I run the server?

After setup, run `fastmcp dev` from the command line.

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