motion-previs-mcp
Enables AI agents to import video footage, trim ranges, run motion analysis (camera, actor, object, or full scene), export depth passes and pose data, and send layers to the Blockout previs app via Motion Previs Studio.
README
motion-previs-mcp
MCP (Model Context Protocol) stdio bridge for Motion Previs Studio — the open-source desktop app that turns real reference footage into AI-generator control packs. With this server connected, an AI agent can import a shot (local file or URL), trim the range, pick what to preserve (camera move, actor performance, object motion, or the full scene), run the analysis pipeline, watch its progress, export the bundle (depth passes, OpenPose skeleton video + keypoints, camera path, prompts), and send layers straight to the Blockout previs app.
Zero dependencies. Node ≥ 18. One file.
Requirements
- Motion Previs Studio v4.1+ must be running. Get it from the app repo (build from source or use a release DMG).
- On launch, the app starts a localhost-only control server on a random port and writes a discovery file to
~/.config/motion-previs/control.json(random bearer token, mode 0600, removed on quit). This bridge reads that file automatically — nothing to configure, no credentials to enter.
Connect
Hermes
Add to ~/.hermes/config.yaml (or install from the Hermes MCP catalog once listed):
mcp_servers:
motion-previs:
command: "node"
args: ["/absolute/path/to/motion-previs-mcp/motion-previs-mcp.mjs"]
Claude Code
claude mcp add motion-previs -- node /absolute/path/to/motion-previs-mcp/motion-previs-mcp.mjs
Any MCP client (generic stdio config)
{ "mcpServers": { "motion-previs": { "command": "node", "args": ["/absolute/path/to/motion-previs-mcp/motion-previs-mcp.mjs"] } } }
Tools (11)
get_state · import_file · import_url · set_range · set_mode · set_settings · run_analysis · export_pack · list_bundle · send_to_blockout · screenshot
The agent workflow: import_file/import_url → set_range + set_mode (camera_only | actor_motion | object_motion | full_scene) → run_analysis → poll get_state until analysis.status is done → export_pack → optionally send_to_blockout (reference / depth / ai_depth / pose / openpose).
Security
The app's control server binds to 127.0.0.1 only, uses a per-launch random bearer token, and validates every action against a whitelist. Nothing is exposed off-machine.
License & credit
Apache-2.0 — see LICENSE. Per the NOTICE file, use, forks, and redistribution must credit Sam Wasserman (wassermanproductions.com).
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.