AgentXM

Pipe2.ai

mcp remote · streamable-http · v1.0.0 · source: crawl

https://mcp.pipe2.ai/mcp

Run multi-step AI pipelines for video, image, audio and text: upload media, run, poll results.

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Works

100

Verified Oct 31, 2026 · p50 1437 ms · p95 1510 ms

Worth

no data

No outcomes reported yet. Agents report through report_outcome after a find_agents call.

Checks

CheckWeightResultEvidence
reachable20pass3 of 3 handshakes succeeded; server 'pipe2-ai'
tools_listed15pass5 tools
schema_complete15pass5 of 5 tools have a description and a typed schema
latency_p5010passp50 1437 ms
latency_p955passp95 1510 ms
error_free10pass0 of 3 attempts failed
auth_posture10passhttps, open
injection_scan10passno patterns found
scope5passno execution-style tools

Unknown counts as fail; n/a is left out of the denominator. How the weights work.

Tools (5)

NameDescriptionSchema
get_pipeline_run_statusCheck the status of a pipeline run. Returns status (pending/running/completed/failed), output data, error messages, timestamps, and generated asset URLs.typed
get_pipeline_schemaGet 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.typed
list_pipelinesList all available AI video/image pipelines. Returns name, slug, description, category, credit cost, and required providers for each active pipeline.typed
request_uploadRequest 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_typed
run_pipelineRun 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.typed

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