ai.pipe2/mcp · v1.0.0 · ai-and-media
Pipe2.ai is healthy: it completed an MCP handshake in 1462 ms and exposes 5 tools. It scores 60/100.
Run multi-step AI pipelines for video, image, audio and text: upload media, run, poll results.
Endpoint: https://mcp.pipe2.ai/mcp (streamable-http)
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| health | 20.2 / 25 |
| authEase | 15 / 15 |
| toolQuality | 15 / 15 |
| maintenance | 5 / 15 |
| adoption | 0 / 10 |
| usage | 0 / 10 |
| security | 5 / 10 |
Scoring v0.3, computed 2026-10-14T14:16:22.083Z.
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-14T11:15:34.341Z | Healthy | 1462 |
get_pipeline_run_status | Check the status of a pipeline run. Returns status (pending/running/completed/failed), output data, error messages, timestamps, and generated asset URLs. |
get_pipeline_schema | Get the input schema for a specific pipeline. Returns the JSON Schema describing required and optional input fields. Use this before running a pipeline to understand what inputs are needed. |
list_pipelines | List all available AI video/image pipelines. Returns name, slug, description, category, credit cost, and required providers for each active pipeline. |
request_upload | Request a presigned S3 upload URL for a file. Use this for pipeline inputs that require file URLs (e.g., images, videos, audio). **Two-step upload flow:** 1. Call this tool with filename and content_type to get a presigned upload URL and final asset URL 2. PUT the file contents to the upload_url (p |
run_pipeline | Run an AI pipeline by slug with the given input. Use list_pipelines to discover available pipelines and get_pipeline_schema to see required inputs. Returns a run ID for tracking status. |