MCP server for TikTok data extraction, discovery, search, and transcription
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# TikTok MCP Server A [Model Context Protocol](https://modelcontextprotocol.io) server that lets an AI agent read public TikTok data: **search**, **profiles**, **videos**, **discovery**, **comments**, and **transcription**. There is no TikTok developer account to apply for and no OAuth flow. Everything comes off public pages, so the only credential you might enter is a key for your own transcription endpoint. It runs on any MCP client (Claude, Cursor, opencode, Codex) and returns structured output (`structuredContent` + `outputSchema`) from every tool. Transcription works against any OpenAI-compatible speech-to-text endpoint: Groq, OpenAI, or a Whisper server you host yourself. ## Quick start Paste this into your MCP client config. There is nothing to install first: [`uvx`](https://docs.astral.sh/uv/) fetches the package and runs it on the initial launch. ```json { "mcpServers": { "tiktok": { "type": "stdio", "command": "uvx", "args": ["tiktok-mcp-server"], "env": { "TRANSCRIBE_API_URL": "https://api.groq.com/openai/v1", "TRANSCRIBE_API_KEY": "your-key" } } } } ``` Things worth knowing before the first call: - The `env` block exists only for `transcribe_video`. Write `"env": {}` if you want the other five tools and nothing else. The endpoint must serve an OpenAI-compatible `POST /audio/transcriptions` route backed by a speech-to-text model such as `whisper-large-v3`. - The first tool call downloads Playwright Chromium once, about 150 MB. ffmpeg ships with the package (`imageio-ffmpeg`); set `FFMPEG_PATH` if you'd rather use your own binary. - You need [uv](https://docs.astral.sh/uv/getting-started/installation/) on the machine, since it provides `uvx`. Python 3.11+ comes along with it; uv installs that itself. - **Linux only:** headless Chromium needs system libraries that `uvx` can't install for you. On a fresh machine or Docker image, run this once (it may prompt for `sudo`): ```bash uvx --fro…
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