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Agent.ai MCP Server

Agent.ai MCP Server

Local
github.com/OnStartupsAI & Agents4Updated 86w ago

About Agent.ai MCP Server

Agent.ai MCP Server dynamically loads Agent.ai API functions as tools for MCP clients that need web content, page screenshots, or YouTube transcripts. It caches function definitions to reduce API calls.

Key features

  1. 01Dynamically load Agent.ai API functions
  2. 02Scrape or crawl webpage text
  3. 03Capture webpage screenshots
  4. 04Extract YouTube transcripts
  5. 05Cache function definitions

Use cases

  1. 01Extract webpage content for later use
  2. 02Capture a visual record of a webpage
  3. 03Retrieve a YouTube video's transcript
  4. 04Reduce repeated API calls for function definitions

MCP support

Provides MCP clients with tools dynamically loaded from the Agent.ai API, including web text extraction, screenshots, and YouTube transcript retrieval. An Agent.ai API token is required.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"agentai": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"build"
]
}
}
}
Run commanddocker run -i --rm build

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocibuild

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Agent.ai MCP Server

An MCP server implementation that integrates with the Agent.ai API, providing web text extraction, web screenshots, and YouTube transcript capabilities through a dynamic function loading system.

Features

  • Dynamic Function Loading: Automatically fetches available functions from Agent.ai API
  • Web Text Extraction: Scrape or crawl web pages for text content
  • Web Screenshots: Capture visual screenshots of web pages
  • YouTube Transcripts: Extract transcripts from YouTube videos
  • Caching: Efficient caching of function definitions to reduce API calls

Tools

The server dynamically loads tools from the Agent.ai API. The currently available tools include:

  • grab_web_text

    • Extract text content from web pages
    • Inputs:
      • url (string, required): URL of the web page to extract
      • mode (string, optional): "scrape" for one page, "crawl" for up to 100 pages
  • grab_web_screenshot

    • Capture visual screenshots of web pages
    • Inputs:
      • url (string, required): URL of the web page to capture
      • ttl_for_screenshot (integer, optional): Cache expiration time in seconds
  • get_youtube_transcript

    • Fetch transcripts from YouTube videos
    • Inputs:
      • url (string, required): URL of the YouTube video

and dozens of other tools. To see all available tools, visit https://docs.agent.ai/api-reference.

Configuration

Getting an API Token

To use this MCP server, you'll need an Agent.ai API token. Contact Agent.ai to obtain your token.

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

Docker
{
  "mcpServers": {
    "agentai": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "API_TOKEN",
        "mcp/agentai"
      ],
      "env": {
        "API_TOKEN": "YOUR_API_TOKEN_HERE"
      }
    }
  }
}
NPX
{
  "mcpServers": {
    "agentai": {
      "command": "npx",
      "args": [
        "-y",
        "@agentai/mcp-server"
      ],
      "env": {
        "API_TOKEN": "YOUR_API_TOKEN_HERE"
      }
    }
  }
}

API Usage Examples

Extract Web Text
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: '{"url":"https://agent.ai","mode":"scrape"}'
};

fetch('https://api-lr.agent.ai/v1/action/grab_web_text', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));
Capture Web Screenshot
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: '{"url":"https://agent.ai","ttl_for_screenshot":86400}'
};

fetch('https://api-lr.agent.ai/v1/action/grab_web_screenshot', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));
Get YouTube Transcript
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: '{"url":"https://youtube.com/watch?v=example"}'
};

fetch('https://api-lr.agent.ai/v1/action/get_youtube_transcript', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));

Build

Docker build:

docker build -t mcp/agentai:latest .

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

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