RTK Motion Intelligence — MCP Server
MCP serverSecurityThis integration connects your AI to motion and security data tools covering motion capture, rehab biomechanics, threat intelligence, and fleet vision. Once added, your AI can analyze movement and security data across 21 tools, with 10 free and the rest paid through x402 or USDC.
Use RTK Motion Intelligence — MCP Server in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add RTK Motion Intelligence — MCP Server and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use RTK Motion Intelligence to browse catalog
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
Details
Available today. Use it from your connected AI after setup.
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
After adding it, ask your AI to examine the data you have, such as motion capture recordings or threat intel. Ten tools are free to try, and paid tools are handled through x402 or USDC.
What your AI can do with it
- Analyze motion capture data
- Evaluate rehab biomechanics
- Gather threat intelligence
- Work with fleet vision data
- Start with 10 free tools and pay for the rest via x402 or USDC
Install RTK Motion Intelligence — MCP Server
The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.
Claude Code
claude mcp add --transport http --scope user rtk-motion-intelligence-mcp-serv 'https://api.rtkmotion.io/mcp'Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://api.rtkmotion.io/mcpAdd a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=rtk-motion-intelligence-mcp-serv&config=eyJ1cmwiOiJodHRwczovL2FwaS5ydGttb3Rpb24uaW8vbWNwIn0=Open the link and Cursor adds the server at that address.
ChatGPT
https://api.rtkmotion.io/mcpIn Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add rtk-motion-intelligence-mcp-serv --url 'https://api.rtkmotion.io/mcp'Run it once, then sign in with codex mcp login rtk-motion-intelligence-mcp-serv if the server asks for an account.
From the project's README
As published by rtkmotion/motion-intelligence in README.md.
Agent-to-agent paid data marketplace. Two-person (dyadic) motion capture in a shared coordinate frame, rehab biomechanics, threat intelligence, and commercial-carrier truck-sighting intelligence (RTK Spotter). 21 MCP tools, gasless USDC payments via x402 (EIP-3009).
rtkmotion.io · Developer docs · Live catalog · Pricing · Shared-frame mocap spec
What is this?
A live, hosted Model Context Protocol server providing agent-to-agent paid access to:
- 4D Motion Capture — BVH skeletal animation, multi-view video, robot-ready joint trajectories (NPZ). Two-person (dyadic) capture in a shared coordinate frame: both actors' global root translation and orientation are preserved in one capture-volume frame, so contact, separation and relative pose are recoverable directly from the files. Most released datasets canonicalize each actor to its own origin, which destroys inter-actor geometry irreversibly — see the specification and its pre-purchase verification procedure
- Rehabilitation Biomechanics — cross-exercise summaries, per-exercise reports, ROM and asymmetry metrics
- Location Threat Intelligence — confidence-scored alerts, event distribution, temporal context
- RTK Spotter — Commercial Vehicle Intelligence — de-identified commercial-carrier truck sightings (per-USDOT bundles) plus a geo-stripped truck-recognition CV/OCR training corpus. Commercial carriers only; faces + bystander plates blurred; FMCSA-public labels (USDOT, carrier, equipment)
The server runs at https://api.rtkmotion.io/mcp on Cloudflare Workers, using the streamable-HTTP MCP transport.
This repository is the public-facing manifest for catalog discovery. The server itself is hosted, not installable from this repo.
Quick start
Add to Claude Desktop / Cursor / Cline / Continue
Add to your client's MCP config (e.g. ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"rtk-motion": {
"type": "streamable-http",
"url": "https://api.rtkmotion.io/mcp"
}
}
}
Restart your client. The 21 tools become available.
See examples/ for ready-to-use config snippets and a minimal Python connect script.
Free tools (no payment, 10 total)
browse_catalog— hierarchical catalog of all datasearch_catalog— full-text search across motion capture, rehab, threat, and Spotter datasetsget_mocap_sample— first 5 s of BVH skeletal animation (300 frames at 60 fps)get_calibration— multi-camera capture-rig calibrationget_threat_profile— monitored location profile (assets, feeds, scan interval)get_threat_sample— current threat assessment sampleget_rehab_profile— patient demographics, injury history, medicationsget_rehab_sample— rehab biomechanics sampleget_spotter_carrier_profile— commercial-carrier coverage + de-identification postureget_spotter_cv_profile— truck CV/OCR corpus profile (image count, label schema)
Paid tools (USDC via x402, 11 total)
| Tool | Price | Output |
|---|---|---|
get_bvh | $10 | Full BVH skeletal animation |
get_video_url | $5 | Multi-view grappling video |
get_robotarget | $15 | Robot-ready joint trajectories (NPZ, MoveIt/ROS/Isaac compatible) |
get_trial_bvh | $0.25 | Trial BVH slice (5 s) — evaluate quality |
get_trial_robotarget | $0.25 | Trial NPZ trajectory (5 s) — evaluate quality |
get_threat_summary | $0.50 – $1.00 | Location threat assessment (lite / full) |
get_rehab_summary | $0.50 | Cross-exercise biomechanical summary |
get_rehab_report | $0.25 | Per-exercise biomechanical report |
get_spotter_carrier | $5 | Per-USDOT commercial-carrier sighting bundle (de-identified crops + trail) |
get_spotter_cv_sample | $0.25 | Trial slice of the truck CV/OCR corpus |
get_spotter_cv | $50 | Full geo-stripped truck-recognition CV/OCR training corpus |
Payment in USDC via the x402 payment protocol. Which networks are available depends on the flow:
| Flow | Networks | How |
|---|---|---|
Gasless x402 exact / EIP-3009 (preferred) | Base | Agent signs a single-use transfer authorization and passes it as x_payment — no gas for the buyer |
On-chain payment_tx (legacy, MCP tools) | Base · Ethereum · Solana | Send USDC, then supply the settled transaction hash |
HTTP /paid/* routes | Base only | CDP-facilitated; the 402 challenge advertises eip155:8453 |
Full pricing detail at api.rtkmotion.io/pricing.
Provenance
Every paid record is signed with ECDSA (secp256k1) by 0x6C11F8a21f7ca922F483Ed21C3b6c2d9B305B10C. Verification key (JWKS) at api.rtkmotion.io/.well-known/jwks.json.
Discovery surfaces
| Surface | URL |
|---|---|
| Website | rtkmotion.io · developer docs |
| Glama connector | glama.ai/mcp/servers/RTKMotion/motion-intelligence |
| Smithery catalog | smithery.ai/servers/RTKMotion/motion-intelligence |
| MCP Server Registry | io.rtkmotion/data (listing) |
| A2A Agent Card | api.rtkmotion.io/.well-known/agent.json |
| x402 Manifest | api.rtkmotion.io/.well-known/x402 |
| OpenAPI 3.1 | api.rtkmotion.io/openapi.json |
| Live data catalog (free) | api.rtkmotion.io/catalog |
Use cases
- Robotics — Motion capture for sim-to-real kinematic retargeting (MoveIt/ROS/Isaac compatible NPZ trajectories). Dyadic captures support two-person interaction and contact-rich manipulation work that single-actor corpora cannot express
- Human interaction / HOI modelling — Two-person motion in one shared coordinate frame, so contact, separation and relative pose are recoverable per frame rather than approximated
- Insurance / Underwriting — Validate rehab claims with objective biomechanical data; assess facility risk via threat intelligence; vet commercial carriers via Spotter sighting bundles
- Physical Therapy — Track patient progress with per-exercise biomechanical reports
- Security & Compliance — Location threat audits, confidence-scored alerting
- Fleet & Logistics / Computer Vision — Commercial-carrier movement corroboration and cargo-fraud investigation from de-identified truck sightings; train truck-recognition detection/OCR models on the geo-stripped CV corpus
Latency
< 500 ms typical for free tools. Cloudflare Workers global edge deployment.
Specifications
- Shared-Frame Multi-Actor Motion Capture — a delivery specification
— a vendor-neutral spec for delivering multi-actor mocap without destroying
inter-actor geometry, with a pre-purchase verification procedure a buyer can
run against any supplier. Draft, published for comment.
Canonical URL:
https://github.com/RTKMotion/motion-intelligence/blob/main/docs/SHARED_FRAME_MOCAP_SPEC.md
Source
This is a manifest repository for the hosted MCP server. The server implementation runs on Cloudflare Workers; the implementation source is private. For technical questions, partnership, or custom integration: support@rtkmotion.io.
License
The contents of this repository (README, examples, configuration files) are released under the MIT License — see LICENSE.
The data products served by the MCP server are separately licensed via the per-purchase terms documented at api.rtkmotion.io/.well-known/x402 and at rtkmotion.io/legal.
Tools it offers (21)
What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.
browse_catalogget_bvhget_video_urlget_robotargetget_trial_bvhget_trial_robotargetsearch_catalogget_threat_summaryget_threat_profileget_rehab_summaryget_rehab_reportget_rehab_profileget_threat_sampleget_rehab_sampleget_mocap_sampleget_calibrationget_spotter_carrier_profileget_spotter_carrierget_spotter_cv_profileget_spotter_cvget_spotter_cv_sample
Signals
- GitHub stars
- 1
- Last commit
- Aug 2026
Advanced
- Delivery
- data MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
io-rtkmotion-data- Source
- github.com/rtkmotion/motion-intelligence
- Hosted endpoint
https://api.rtkmotion.io/mcp
github.com/rtkmotion/motion-intelligence
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