fiftyone-mcp-server

@AdonaiVera/fiftyone-mcp-server

0 Stars 2 次浏览 AdonaiVera 更新于 2026-08-23

Control FiftyOne computer vision datasets through AI assistants using 80+ operators.

MCP 服务配置

复制以下 JSON 到 OPClaw 或其他 MCP 客户端的配置文件中即可使用

{
  "mcpServers": {
    "fiftyone-mcp-server": {
      "args": [
        "fiftyone-mcp-server@0.1.2"
      ],
      "command": "uvx"
    }
  }
}

可用工具（5 个）

该服务在 MCP 协议中暴露的工具，AI 可按需调用

tavily_search 14 个参数需填 1 项 Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

必填参数：query

tavily_extract 6 个参数需填 1 项 Extract content from URLs. Returns raw page content in markdown or text format.

Extract content from URLs. Returns raw page content in markdown or text format.

必填参数：urls

tavily_crawl 11 个参数需填 1 项 Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

必填参数：url

tavily_map 8 个参数需填 1 项 Map a website's structure. Returns a list of URLs found starting from the base URL.

Map a website's structure. Returns a list of URLs found starting from the base URL.

必填参数：url

tavily_research 2 个参数需填 1 项 Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

必填参数：input

服务介绍

FiftyOne MCP Server

<!- - mcp-name: io.github.voxel51/fiftyone-mcp-server - ->

<!- - prettier-ignore - ->

Control FiftyOne datasets through AI assistants using the Model Context Protocol

Documentation · FiftyOne Skills · FiftyOne Plugins · Discord

# What is the FiftyOne MCP Server?

Enable Agents to explore datasets, execute operators, and build computer vision workflows through natural language. This server exposes FiftyOne's operator framework (80+ built-in operators) through 16 MCP tools.

"List all my datasets"
"Load quickstart dataset and show summary"
"Find similar images in my dataset"

The server starts with 50 built-in operators. Install plugins to expand functionality - the AI can discover and install plugins automatically when needed (brain, zoo, annotation, evaluation, and more).

# Available Tools

Design Philosophy: Minimal tool count (16 tools), maximum flexibility (full operator & plugin ecosystem).

# Quick Start

# # Step 1: Install the MCP Server

pip install fiftyone-mcp-server

⚠️ Important: Make sure to use the same Python environment where you installed the MCP server when configuring your AI tool. If you installed it in a virtual environment or conda environment, you must activate that environment or specify the full path to the executable.

# # Step 2: Configure Your AI Tool

claude mcp add fiftyone - - fiftyone-mcp

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "fiftyone": {
      "command": "fiftyone-mcp"
    }
  }
}

Install in Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "fiftyone": {
      "command": "fiftyone-mcp"
    }
  }
}

Add to .vscode/mcp.json:

{
  "servers": {
    "fiftyone": {
      "command": "fiftyone-mcp"
    }
  }
}

Edit ~/Library/Application Support/ChatGPT/config.json:

{
  "mcpServers": {
    "fiftyone": {
      "command": "fiftyone-mcp"
    }
  }
}

If you have uv installed:

{
  "mcpServers": {
    "fiftyone": {
      "command": "uvx",
      "args": ["fiftyone-mcp-server"]
    }
  }
}

This downloads and runs the latest version automatically.

# # Step 3: Use It

"List all my datasets"
"Load quickstart dataset and show summary"
"What operators are available for managing samples?"
"Set context to my dataset, then tag high-confidence samples"
"What plugins are available? Install the brain plugin"
"Find similar images in my dataset"

Claude will automatically discover operators and execute the appropriate tools.

# Contributing

We welcome contributions! Here's how to set up a local development environment:

Clone the repository

git clone https://github.com/voxel51/fiftyone-mcp-server.git
cd fiftyone-mcp-server

Install dependencies
```
poetry install
```
Run the server locally
```
poetry run fiftyone-mcp
```

Test your changes

poetry run pytest
poetry run black -l 79 src/
npx @modelcontextprotocol/inspector poetry run fiftyone-mcp

Submit a Pull Request

# Resources

# Community

Join the FiftyOne community to get help, share your ideas, and connect with other users:

Discord: FiftyOne Community
GitHub Issues: Report bugs or request features

查看源码项目主页

MCP 服务配置

可用工具 （5 个）