AI Video Check MCP Server
Allows checking videos at public Facebook links for AI-generation probability, returning separate picture and sound scores.
Allows checking videos at public Instagram links for AI-generation probability, returning separate picture and sound scores.
Allows checking videos at public TikTok links for AI-generation probability, returning separate picture and sound scores.
Allows checking videos at public YouTube links for AI-generation probability, returning separate picture and sound scores.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AI Video Check MCP Server check if this video is AI-generated: https://youtu.be/dQw4w9WgXcQ"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AI Video Check — MCP server
Let Claude, Cursor or any MCP client check whether a video was generated by AI.
This server connects your AI assistant to AI Video Check, a detector for AI-generated video (Sora, Veo, Kling, MiniMax, HeyGen and others). Give it a link or a local file, and it returns the probability of AI generation with separate scores for the picture and the sound.
It is a thin layer over the public AI Video Check API: the same key, the same credits and the same results.
Tools
Tool | What it does | Cost |
| Checks the video at a public link (TikTok, Instagram, X, YouTube, Facebook or a direct file URL). Waits up to about a minute for the result. | 1 credit per started minute of video |
| Returns the result of an earlier check. Results are kept for 24 hours. | free |
| Shows the remaining credits and the limits of your key. | free |
| Checks a video file on your own computer. Local mode only. | 1 credit per started minute of video |
Every result tells the assistant how to read it: a probability, not proof. A low score means no signs of generation were found, not that the video is authentic. Editing, visual effects and face swaps on real footage are not detected.
Related MCP server: MnogoReels MCP server
Get a key
Sign in at aivideocheck.net and confirm your e-mail.
Open Dashboard → API and create a key. It is shown once.
Your first key comes with 20 free credits for the API.
Keep the key secret. Anyone holding it spends your credits. You can revoke a key on the same page; it stops working within a minute.
Connect: remote server (links)
The server runs at https://api.aivideocheck.net/mcp (Streamable HTTP). Your client sends the key in the Authorization header.
Claude Code
claude mcp add --transport http aivideocheck https://api.aivideocheck.net/mcp --header "Authorization: Bearer avc_live_..."Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"aivideocheck": {
"url": "https://api.aivideocheck.net/mcp",
"headers": { "Authorization": "Bearer avc_live_..." }
}
}
}Any other client that supports Streamable HTTP with custom headers works the same way.
Connect: local server (links and files on your computer)
The local server runs on your machine and can also check video files from your disk. It uploads them to AI Video Check for analysis, exactly as the website does; files are deleted when the check ends.
git clone https://github.com/aivideocheck/aivideocheck-mcp
cd aivideocheck-mcp
python -m venv .venv
.venv/bin/pip install -r requirements.txt # Windows: .venv\Scripts\pipThen point your client at it, for example Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"aivideocheck": {
"command": "/path/to/aivideocheck-mcp/.venv/bin/python",
"args": ["/path/to/aivideocheck-mcp/avc_mcp.py"],
"env": { "AVC_API_KEY": "avc_live_..." }
}
}
}check_file sends only files that are named and built like a video container (MP4, MOV, WebM, MKV, AVI and similar). Anything else stays on your computer, so an instruction hidden in a web page cannot make your assistant upload, say, your SSH key.
Configuration
Variable | Default | Meaning |
| — | Your key. Read in local mode only; the remote server never uses a key from its own environment. |
|
| API address. |
|
| How long |
Development
.venv/bin/python tests/test_mcp.pyThe test runs the server against a fake API on 127.0.0.1, over real HTTP and real stdio, with the MCP SDK's own client. It does not touch the live service.
Pricing and terms
Checks spend the same credits as the website: one credit per started minute of video. Prices are on the developer page. Use of the API is governed by the Terms of Service and the Privacy Policy.
Questions: support@aivideocheck.net
License
MIT — see LICENSE.
Available Tools
4 toolscheck_fileCheck a video fileAInspect
Check whether a video file on this computer was generated by AI. Uploading the original file gives a more reliable result than a link. Spends credits: one per started minute of video.
Inputs: path (required). Returns: result
check_videoCheck a video by linkAInspect
Check whether the video at a public link (TikTok, Instagram, X, YouTube, Facebook or a direct file URL) was generated by AI. Spends credits: one per started minute of video. Waits up to about a minute; if the check is not done by then, returns its id for get_check.
Inputs: url (required). Returns: result
get_balanceCredit balanceARead-onlyInspect
Show how many AI Video Check credits the account has left and the limits of its key. Free.
Inputs: no named parameters. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
check_video and check_file both detect AI-generated video and differ only by input source (public link vs local file), which the descriptions make clear but still requires reading carefully. get_check and get_balance have clearly distinct roles (retrieve result vs account status), so overlap is limited to the two check tools.
All four names follow a strict verb_noun snake_case pattern (check_video, check_file, get_check, get_balance). The verbs are used coherently: check_ for initiating analysis, get_ for retrieving information.
Four tools is well-scoped for a focused detection service: two submission paths, one result retrieval, and one account query. Every tool earns its place with no redundancy or padding.
The submit/retrieve/balance lifecycle is covered, including both URL and file inputs. Minor gaps exist: no way to list or cancel prior checks, and results expire after 24 hours without a cleanup or history operation.
Maintenance
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