Uploadcheck MCP server
{
"mcpServers": {
"uploadcheck": {
"command": "npx",
"args": [
"-y",
"@drantoniou/uploadcheck-mcp@latest"
],
"env": {
"UPLOADCHECK_API_BASE_URL": "https://...",
"UPLOADCHECK_API_KEY": "<uploadcheck_api_key>",
"YOUR_KEY": "<your_key>"
}
}
}
}{
"mcpServers": {
"uploadcheck": {
"command": "npx",
"args": [
"-y",
"@drantoniou/uploadcheck-mcp@latest"
],
"env": {
"UPLOADCHECK_API_BASE_URL": "https://...",
"UPLOADCHECK_API_KEY": "<uploadcheck_api_key>",
"YOUR_KEY": "<your_key>"
}
}
}
}{
"mcpServers": {
"uploadcheck": {
"command": "npx",
"args": [
"-y",
"@drantoniou/uploadcheck-mcp@latest"
],
"env": {
"UPLOADCHECK_API_BASE_URL": "https://...",
"UPLOADCHECK_API_KEY": "<uploadcheck_api_key>",
"YOUR_KEY": "<your_key>"
}
}
}
}{
"servers": {
"uploadcheck": {
"command": "npx",
"args": [
"-y",
"@drantoniou/uploadcheck-mcp@latest"
],
"env": {
"UPLOADCHECK_API_BASE_URL": "${input:uploadcheck_api_base_url}",
"UPLOADCHECK_API_KEY": "${input:uploadcheck_api_key}",
"YOUR_KEY": "${input:your_key}"
}
}
},
"inputs": [
{
"id": "uploadcheck_api_base_url",
"type": "promptString",
"description": "Uploadcheck api base url",
"password": true
},
{
"id": "uploadcheck_api_key",
"type": "promptString",
"description": "Uploadcheck api key",
"password": true
},
{
"id": "your_key",
"type": "promptString",
"description": "Your key",
"password": true
}
]
}{
"mcpServers": {
"uploadcheck": {
"command": "npx",
"args": [
"-y",
"@drantoniou/uploadcheck-mcp@latest"
],
"env": {
"UPLOADCHECK_API_BASE_URL": "https://...",
"UPLOADCHECK_API_KEY": "<uploadcheck_api_key>",
"YOUR_KEY": "<your_key>"
}
}
}
}file .mcp.json (in your project root)file claude_desktop_config.jsonfile ~/.cursor/mcp.jsonfile .vscode/mcp.jsonfile ~/.codeium/windsurf/mcp_config.jsoninstall npx -y @drantoniou/uploadcheck-mcpversion 0.1.1
What it does
UploadCheck is a quality control service that analyzes videos, podcasts, and clips for technical issues before upload. It returns timestamped flags with specific repair guidance, allowing AI agents and editors to fix problems programmatically rather than discovering them after publication.
- Check a finished video export for audio dropouts, frozen frames, sync drift, and caption safety violations before publishing to social media.
- Integrate quality gates into an AI video generation pipeline so the agent can automatically repair flagged issues and re-check instead of shipping broken media.
- Generate editor marker CSVs from quality flags so timeline issues can be addressed in your NLE before final export.
Tools this server exposes
| Tool | Does |
|---|---|
| qc_estimate_cost | Estimate how many checked minutes and gates will be consumed before running a check. |
| qc_run_local_file | Check a local video or audio file by reading it and sending it to the UploadCheck API. |
| qc_run_video | Check a video from a YouTube URL, signed URL, upload ID, or base64 payload. |
| qc_get_job | Poll the status and progress of a running check job. |
| qc_get_report | Retrieve the finished quality report with verdict, timestamped flags, and evidence. |
| qc_get_events | Fetch lifecycle events from a check to see what gates ran and explain results to users. |
| qc_get_artifacts | List generated report artifacts available for download. |
| qc_get_marker_csv | Export flagged issues as an editor marker CSV for direct import into a non-linear editor timeline. |
| qc_create_upload_url | Generate a signed upload URL for sending large files to UploadCheck. |
Before you enable it
An MCP server runs with whatever access you give it. Start with a development account rather than production, and check which tools the server exposes before you let an agent call them unattended.