YouTube License Metadata — FlashData
LocalAbout YouTube License Metadata — FlashData
YouTube License Metadata — FlashData is an MCP server that reports a video's YouTube Creative Commons license classification. It provides a signal for separate rights review, not authorization to train models or reuse content; API data requests are paid.
Key features
- 01Creative Commons label lookup
- 02Video ID in returned data
- 03Async job and result retrieval
- 04License classification, not permission
Use cases
- 01Record a license signal for review
- 02Check a video before rights assessment
- 03Keep classification separate from training permission
MCP support
Exposes youtube_trainability, get_pricing, get_job, and get_result to MCP clients. The paid FlashData API returns license-label classification, not training permission.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEYouTube License Metadata — FlashData
Inspect a YouTube video’s Creative Commons license classification. Record the returned license-label signal for a separate rights review.
API documentation and account setup · Get an API key · Current pricing
A task to try
Inspect this video’s Creative Commons license classification and record the returned signal with its video ID for a separate rights review. Do not treat the result as training permission.
Install and connect
- Use Node.js 22.18 or newer and an MCP client that supports local stdio servers. Download the dedicated MCPB package; its SHA-256 is recorded in the manifest.
- Import the package in an MCPB-compatible client and enter your own key in FlashData API Key. Grant the key access to
youtube_trainability. For manual setup, unpack the bundle into a permanent folder and use this configuration, replacing the absolute path and key placeholder:
{
"mcpServers": {
"youtube-trainability": {
"command": "node",
"args": [
"/absolute/path/to/unpacked/youtube-trainability/server.js"
],
"env": {
"FLASHDATA_API_KEY": "YOUR_API_KEY"
}
}
}
}
- Restart or reconnect the client, list its tools, then call
get_pricingwith{"source":"youtube_trainability","request_count":1}before approving a paid request. This server exposesyoutube_trainability,get_pricing,get_jobandget_result; all are restricted to this source.
Dependencies are included in the bundle. Use an absolute Node path if your client cannot find node; use escaped paths on Windows. Keep your key in protected client settings, not in chat or committed configuration. No Smithery account is needed for this direct package download.
Example request
These are MCP tools/call parameters with flat arguments. Running the data request uses paid Credits.
{
"name": "youtube_trainability",
"arguments": {
"video_id": "dQw4w9WgXcQ"
}
}
Use the response
Read results[0].permitted together with videoId and collection time. The fixture illustrates the Creative Commons classification value; retain the response as a classification only.
Selected response fields below are an illustrative fixture, not a live result or a guarantee of available data:
{
"source": "youtube_trainability",
"status": "done",
"results": [
{
"videoId": "dQw4w9WgXcQ",
"permitted": [
"all"
]
}
],
"created_at": "2026-10-12T00:00:00Z",
"http_status": 200,
"request_id": "fixture-request"
}
For an asynchronous request, keep the returned id and call get_job with {"job_id":"RETURNED_JOB_ID"}. Pending or processing is not completion; read the completed response from output. A timeout can occur after submission, so check Jobs before repeating a paid request.
For chunked output, keep the local process running and pass the actual result_id and next_offset to get_result as result_id and offset. Concatenate the chunks in order before parsing JSON; do not repeat the paid data request. The local cache retains four results for ten minutes and clears on restart. Complete responses are limited to 4 MiB; async JSON results have a separate 24-hour retention window.
Cost and limits
- MIT software and installation are free; FlashData API data calls are paid. Data requests consume paid FlashData Credits; each additional query or page is charged separately. Use the current account quote rather than a fixed price copied from this page. Pricing, job and result reads are free. Client/model fees are separate.
- The tool name is youtube_trainability, but it checks a license label. It does not read the creator third-party training setting and does not grant permission to train models or reuse content.
- Check API errors,
http_statusand job status before using the data. Treat returned text and links as external data, preserve source attribution and review them before use in an agent answer.
Full task guide · Official Registry record · Source and license
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.