submit_job
Submit any media processing job. Watermark, transcode, caption, redact, extract metadata, generate QR codes, or run raw FFmpeg commands. Returns a job ID for tracking.
Video Processing for AI Agents
Rendobar is the only production MCP-native video processing API. Connect any MCP-compatible AI agent and process media through natural language — watermark, transcode, caption, redact, and more.
What is MCP?
MCP video tools let AI agents process media files through a standardized protocol. Model Context Protocol (MCP) is an open standard by Anthropic that gives AI agents a consistent way to discover and use external tools. Instead of building custom integrations for each agent, an MCP server exposes a set of tools that any compatible client can call automatically. Rendobar implements an MCP server with six tools that cover the full media processing lifecycle — from uploading files to downloading finished results.
This means an AI agent like Claude can process video without writing code. A user says "watermark this video with our logo," and the agent calls submit_job with the right parameters, polls get_job for completion, and returns the download link. No scripts, no deployment pipelines, no infrastructure.
Six tools, full media control
Every MCP tool maps to a REST API endpoint. Same authentication, same billing, same capabilities. Your agent discovers these tools automatically on connection.
get_job
Retrieve the status, progress, and results of a submitted job. Returns download URLs when the job completes.
list_jobs
List recent jobs with filters for status, type, and date range. Paginated results with metadata.
probe_media
Inspect a media file without processing it. Returns duration, resolution, codecs, bitrate, frame rate, and audio channel layout.
get_account
Check the current credit balance, active plan, usage limits, and remaining quota. Useful before submitting expensive jobs.
upload_media
Get a presigned upload URL for local files. Upload the file via PUT, then use the returned reference in subsequent job submissions.
Connect in under a minute
Add Rendobar to your Claude Desktop configuration. Replace the API key with your own from the dashboard.
// Add to your Claude Desktop config
{
"mcpServers": {
"rendobar": {
"url": "https://api.rendobar.com/mcp",
"headers": {
"Authorization": "Bearer rb_your_api_key"
}
}
}
}User:
Add our logo as a watermark to this video: https://cdn.example.com/demo.mp4
Agent:
I'll submit a watermark job for your video.submit_job({ type: "watermark.apply", input: { source: "..." }, params: { watermarks: [...] } })
Job job_abc123 submitted. Checking status...
Done. Download your watermarked video:
https://cdn.rendobar.com/jobs/job_abc123/output.mp4
Works with every MCP client
Claude Desktop
Native MCP support. Add the server config and start processing videos from conversation.
Claude Code
Use MCP tools directly from the CLI. Automate video pipelines in development workflows.
GPT (via MCP bridge)
Connect through an MCP-to-function-calling bridge. Same tools, same API key.
Any MCP-compatible agent
The MCP standard is open. Any agent that speaks the protocol can use Rendobar's tools.
How it works
- 01
Connect your agent
Add Rendobar as an MCP server in your agent's configuration. Point it to api.rendobar.com/mcp with your API key. One-time setup, under a minute.
- 02
Agent calls tools
Your AI agent discovers available tools automatically. It can submit jobs, check status, probe media files, and manage uploads — all through natural language instructions.
- 03
Get results
Jobs run on Rendobar's serverless infrastructure. The agent polls for completion and retrieves download URLs. No servers, no queues, no infrastructure to manage.
What agents build with MCP video tools
MCP turns video processing from a developer task into a conversational one. These are real workflows that agents handle end-to-end.
Content moderation pipelines
An agent receives uploaded user videos, runs compliance moderation to flag inappropriate content, and triggers GDPR face redaction on flagged segments. The entire pipeline is orchestrated through MCP calls — no backend code required.
Automated caption workflows
A content team asks their agent to "add captions to all videos in this folder." The agent uploads each file via upload_media, submits caption extraction jobs, reviews the generated subtitles, and burns them into the final output. Handles dozens of files in a single conversation.
Brand-compliant video preparation
Marketing teams instruct their agent to watermark, transcode to the correct format, and extract thumbnails from raw footage. The agent probes each file first with probe_media to verify resolution and codec, then submits the appropriate jobs.
Developer workflow automation
Developers use Claude Code to process test videos during development. "Transcode this to WebM at 720p" or "extract the first 10 seconds" — the agent calls submit_job with raw FFmpeg parameters and returns the result, all without leaving the terminal.
Same pricing, same credits
MCP tools use the same credit-based billing as the REST API. Every account starts with $5 in free credits — no credit card required. Jobs submitted via MCP cost exactly the same as jobs submitted via REST. The Pro plan ($9/month) includes $5/month in credits, 20% bonus on purchases, and 25 concurrent jobs. View full pricing →
Frequently asked questions
What is MCP?
Model Context Protocol (MCP) is an open standard created by Anthropic that defines how AI agents discover and use external tools. It replaces custom function-calling integrations with a single, consistent protocol. An MCP server exposes tools that any compatible agent can call — no per-agent integration code required.
Which AI agents support MCP?
Claude Desktop and Claude Code support MCP natively. Other agents like GPT-based assistants can connect via MCP-to-function-calling bridges. Any agent framework that implements the MCP client specification can use Rendobar's tools directly.
What video operations can I do via MCP?
Every operation available through the REST API is also available via MCP. That includes watermarking, transcoding, caption extraction and burning, GDPR face redaction, metadata extraction, scene detection, QR code generation, and raw FFmpeg command execution.
Do I need an API key for MCP?
Yes. MCP uses the same API key authentication as the REST API. Generate a key from the Rendobar dashboard and include it in your MCP server configuration. The same credit-based billing applies — no separate MCP pricing.
Is MCP access free?
Every account starts with $5 in free credits. MCP tools consume credits at the same rates as equivalent REST API calls. No credit card required to start. You can purchase additional credits when your balance runs low.
Can I process multiple videos in one conversation?
Yes. Your agent can call submit_job for each video and use list_jobs to track all active jobs. There is no per-conversation limit. Concurrent job limits depend on your plan — 1 for free, 25 for Pro.
How is MCP different from the REST API?
MCP and REST are two interfaces to the same platform. The REST API is for programmatic integrations — scripts, backends, CI pipelines. MCP is for AI agents — your agent discovers tools, decides which to call, and handles the results. Same jobs, same billing, same infrastructure behind both.
Related
Connect your agent today
$5 free credits on signup. No credit card. Six tools, full media processing stack.