OpenClip for AI Video Automation Teams | MCP Workflows - OpenClip
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AI Automation Teams

OpenClip for AI Video Automation Teams

Automation teams already orchestrate assistants and agents for text and data; video is usually the holdout that still means a human in a browser. OpenClip's MCP server closes that gap with typed tools (submit_video, list_clips, render_clip) that slot into the same agent stack you run everything else on.

Industry: AI operations
Audience: Automation teams
Plan: Pro

Pain Points

Video work sits outside the automation stack while everything else is agent-driven
Browser agents are too fragile for recurring production tasks like uploads and long processing waits
Editors and operators repeat the same submit, poll, review, and render steps by hand
Output drifts between operators because caption styles and framing are chosen ad hoc
Long recordings pile up unclipped because starting the process requires a human

Assistant-led video intake

1

Connect the team's assistant or agent to https://openclip.app/mcp (OAuth 2.1; header-only agents use a token at /mcp/key)

2

Capture source URL, audience, platform, and clip brief in the request

3

Submit through submit_video (duplicates within 24h reuse the existing run)

4

Let the agent poll get_video_status and post progress to the channel

5

Deliver list_clips results with virality scores for a human approval pass

Standardized batch rendering

1

Define one processing agent via create_agent: caption preset, composition settings, logo

2

Reference that agent in every submit_video call across the team

3

Render approved moments with render_clip and poll get_render_status

4

Skim get_usage weekly for credit burn (minutes) and unexpected activity

Failure-aware operations

1

Instant failed after submit: subscription lapsed, escalate to the account owner

2

pending_credits: top up processing minutes; the job resumes without resubmission

3

download_failed: source URL unfetchable, verify against list_supported_providers

4

Status frozen ~15 minutes: stop polling, retry later, capture the video id for support

Features

Agent-ready video tools

Twenty-eight typed tools cover intake to rendered output, so video becomes one more capability in the agent stack rather than a browser-shaped exception.

Composable job model

Submit, poll, list, render are discrete calls with machine-readable statuses, which is exactly the shape schedulers and agent frameworks want.

Presets end output drift

A shared processing agent pins tracker, captions, and branding, so episode 40 looks like episode 1 no matter who or what submitted it.

Named failures, real runbooks

failed, pending_credits, and download_failed each map to one fix, so on-call automation can route problems without a human diagnosing screenshots.

Credentials that scale down

OAuth per operator, revocable grants, and scoped tokens for headless agents; no shared master key living in a prompt.

Predictable spend

Credits are minutes of processing (300 per month on Pro), queryable via get_usage, with 24h dedup protecting against double-submission burn.

Frequently Asked Questions

Video is the worst case for browser automation: multi-minute processing, uploads, and dynamic UIs. MCP replaces all of it with typed calls and honest statuses, which is why the flakiest part of most automation stacks is the first thing worth migrating.

Pro is the practical starting point: 300 processing minutes per month, up to three processing agents, team workspaces, and priority processing. Teams needing API access or custom volume move to Business.

Agents that can complete OAuth use the standard flow against https://openclip.app/mcp. Header-only agents mint a personal access token in OpenClip and call https://openclip.app/mcp/key; store it in the secret store, not the prompt.

Approving which moments render and reviewing clips before publishing. Everything else, intake through rendering, is safe to hand to the agents.

Make video part of your AI automation stack

Connect OpenClip MCP and turn assistant requests into rendered, captioned clips with a human only where judgment matters.

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