videoseek-mcp

Find anything in any video. Semantic video search, video Q&A, persistent memory, and social media import — all as MCP tools for your AI agent.

What can it do?

Give your AI agent (Claude, Cursor, Windsurf, etc.) the ability to:

• Search videos by meaning — "find the moment where someone opens the gift" across your entire library
• Ask questions about videos — multi-turn conversations with one video or your whole collection
• Remember everything — persistent text + video memory that never forgets (Memory Augmented Generation)
• Import from social media — pull and index content from TikTok, YouTube, Instagram, and 15+ platforms
• Analyze on-the-fly — describe any video or image from URL without uploading
• Transcribe — get visual scene descriptions or spoken word transcripts

Quick Start

1. Get an API Key

Sign up at memories.ai and grab your key from the API keys page. Free tier includes 100 credits/month.

2. Install

git clone https://github.com/kennyzheng-builds/videoseek-mcp.git
cd videoseek-mcp
npm install --include=dev
npm run build

3. Connect to your AI client

Claude Desktop

Add to `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or `%APPDATA%\Claude\claude_desktop_config.json` (Windows):

{
  "mcpServers": {
    "videoseek": {
      "command": "node",
      "args": ["/path/to/videoseek-mcp/build/index.js"],
      "env": {
        "MEMORIES_API_KEY": "your-api-key"
      }
    }
  }
}

Cursor

Add to `.cursor/mcp.json`:

{
  "mcpServers": {
    "videoseek": {
      "command": "node",
      "args": ["/path/to/videoseek-mcp/build/index.js"],
      "env": {
        "MEMORIES_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Code

export MEMORIES_API_KEY="your-api-key"
claude mcp add videoseek -- node /path/to/videoseek-mcp/build/index.js

Tools (18)

Video Management

Search

Video Q&A

Persistent Memory

Vision Analysis

Social Media Import

Resources & Prompts

Resources: `memories://videos` (your library), `memories://memories` (your stored knowledge)

Prompt templates: `analyze-video`, `social-media-research`, `build-knowledge-base`

Example Conversations

"Find a moment"

> You: Find all moments where someone is cooking pasta

>

> Agent uses `search_videos` → returns timestamped video segments

"Understand a video"

> You: What's happening in this video? [URL]

>

> Agent uses `caption_video` → instant analysis without uploading

"Research TikTok"

> You: Research AI trends on TikTok

>

> Agent uses `search_public` → `import_from_url` → `chat_personal` for insights

"Build knowledge"

> You: Summarize all my meeting recordings

>

> Agent uses `list_videos` → `get_transcription` → `add_memory` for key takeaways

How It Compares

Environment Variables

Development

npm install --include=dev
npm run build          # compile TypeScript
npm run dev            # watch mode
npx @modelcontextprotocol/inspector node build/index.js   # test interactively

Architecture

videoseek-mcp/
├── src/
│   ├── index.ts     # MCP server — 18 tools, 2 resources, 3 prompts
│   └── client.ts    # Video understanding API client
├── build/           # Compiled JS (generated)
├── package.json
└── tsconfig.json

TypeScript + Zod schemas + stdio transport. No dependencies beyond MCP SDK.

License

MIT