framefetch

framefetch

Agent-first video-data API + MCP across 6 platforms (YouTube/Shorts, TikTok, Reddit, Instagram, Pinterest): metadata, insights, Whisper transcript, and parametric frames. Pay-per-call via x402 (USDC) or Stripe.

Category
访问服务器

README

<p align="center"> <img src="logo.svg" width="84" height="84" alt="FrameFetch logo"> </p>

<h1 align="center">FrameFetch</h1>

<p align="center"> <b>Any social-video URL → metadata, transcript, insights & frames.</b><br> Agent-first video data API + MCP server. Pay per call, or with x402 (USDC) — no account. </p>

<p align="center"> <a href="https://www.npmjs.com/package/framefetch"><img src="https://img.shields.io/npm/v/framefetch?color=5ee0c0" alt="npm"></a> <a href="https://framefetch.net"><img src="https://img.shields.io/badge/website-framefetch.net-4493f8" alt="website"></a> <a href="https://framefetch.net/status"><img src="https://img.shields.io/badge/status-live-3fb950" alt="status"></a> <img src="https://img.shields.io/badge/license-MIT-9aa7b8" alt="MIT"> </p>


FrameFetch turns one YouTube, YouTube Shorts, TikTok, Instagram Reels, Pinterest, or Reddit video URL into a single JSON response: metadata, engagement insights, a transcript (captions or Whisper), and parametrically-sampled frames (every Nth / 1-per-second / a time range, at any width). Built API-first and MCP-first for AI agents.

This repo is the open-source client + docs. The service itself runs at framefetch.net — you bring a free API key (or pay per call with x402); the backend stays hosted.

Why

An LLM can't watch a video. To reason about one it needs the video turned into text and images first — a transcript, metadata, and a few frames. FrameFetch returns all three from a URL, across six platforms, through one schema.

Install

npm install framefetch

Node 18+ (uses built-in fetch). Get a free key: framefetch.net.

Quick start

import { FrameFetch } from 'framefetch';

const ff = new FrameFetch({ apiKey: process.env.FRAMEFETCH_API_KEY });

const r = await ff.extract({
  url: 'https://www.youtube.com/watch?v=jNQXAC9IVRw',
  fields: ['metadata', 'transcript', 'frames'],
  frames: { mode: 'fps', fps: 1, width: 480 },
});

console.log(r.metadata.title);   // "Me at the zoo"
console.log(r.transcript.text);  // "Alright, so here we are…"
console.log(r.frames.count);     // 19

Scoped helpers

await ff.metadata(url);    // title, author, duration, views, likes…
await ff.transcript(url);  // captions, else Whisper
await ff.frames(url, { mode: 'fps', fps: 1, width: 512 });
await ff.platforms();      // capability matrix (no key)
await ff.status();         // live service health (no key)

No signup

const ff = new FrameFetch();                              // no key
await ff.demo('https://youtu.be/jNQXAC9IVRw');            // instant metadata, rate-limited
const { key } = await ff.createKey('you@example.com');    // self-serve key + free credit

Use it from an MCP agent

FrameFetch ships an MCP server (Streamable HTTP) with the tools framefetch_extract and framefetch_platform_capabilities. Add it to Claude, Cursor, or any MCP client:

{
  "mcpServers": {
    "framefetch": {
      "url": "https://framefetch.net/mcp",
      "headers": { "Authorization": "<YOUR_FRAMEFETCH_KEY>" }
    }
  }
}

Or one line:

claude mcp add --transport http framefetch https://framefetch.net/mcp \
  --header "Authorization: <YOUR_FRAMEFETCH_KEY>"

Local stdio bridge

Prefer a local stdio server (Claude Desktop, sandboxes, no inbound HTTP)? This package ships framefetch-mcp, a zero-dependency stdio↔HTTP bridge that exposes the same tools and forwards calls to framefetch.net:

{
  "mcpServers": {
    "framefetch": {
      "command": "npx",
      "args": ["-y", "framefetch-mcp"],
      "env": { "FRAMEFETCH_API_KEY": "<YOUR_FRAMEFETCH_KEY>" }
    }
  }
}

tools/list works with no key; tool calls use FRAMEFETCH_API_KEY (or x402). Override the endpoint with FRAMEFETCH_MCP_URL.

Pay without an account (x402)

Autonomous agents can pay per call in USDC via x402 on Base — no signup, no human in the loop. Discoverable in the x402 Bazaar and at /.well-known/x402.json. Humans can use a free tier, prepaid credits, or a Stripe card.

Errors

import { FrameFetchError } from 'framefetch';
try {
  await ff.transcript(url);
} catch (e) {
  if (e instanceof FrameFetchError && e.status === 402) {
    // out of credit — top up at framefetch.net or via x402
  }
}

API surface

Method Endpoint Auth
extract({ url, fields, frames }) POST /v1/extract key
metadata(url) POST /v1/metadata key
transcript(url) POST /v1/transcript key
frames(url, spec) POST /v1/frames key
platforms() GET /v1/platforms
status() GET /v1/status
demo(url) POST /v1/demo
createKey(email) POST /v1/keys

Full OpenAPI: framefetch.net/openapi.json · Docs: framefetch.net/docs

Links

Website · Docs · Pricing · Status · Guide: giving an agent video data

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选