# vision.analyze_motion

Return observed motion tracks, compiled curves, and replay bounds.

Agent View of the PolicyLayer registry record for `vision.analyze_motion`. HTML page: https://policylayer.com/tools/visionmcp/vision.analyze-motion

## Facts

- Tool: `vision.analyze_motion`
- Server: Visionmcp (`joshuahickscorp/visionmcp`) — https://policylayer.com/tools/visionmcp.md
- Homepage: https://github.com/joshuahickscorp/visionmcp
- Risk category: Read (Low risk)
- Registry record: grade F, identity unverified
- Server rate-limited: no
- Parameters: 0
- Recommended policy verdict: Allowed

## Example call (MCP tools/call, JSON-RPC 2.0)

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "vision.analyze_motion",
    "arguments": {}
  }
}
```

## Why vision.analyze_motion is rated Low

The verb 'Return' and the nature of the outputs (observed tracks, curves, bounds) indicate this tool queries and retrieves visual analysis data without side effects. There is no creation, modification, deletion, or code execution. This is a straightforward read operation on visual/motion data, appropriate for a visual compiler/analyzer context.

From the tool's own definition: "Tool description states it returns 'observed motion tracks, compiled curves, and replay bounds' — purely data retrieval operations with no modification, deletion, or execution of external processes."

## Use case

AI agents call vision.analyze_motion to retrieve information from Visionmcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

## Recommended policy (PolicyLayer)

Verdict: **Allowed**. Enforced by the PolicyLayer MCP gateway (https://policylayer.com/mcp-gateway) before a call reaches Visionmcp:

```json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "vision.analyze_motion": {}
  }
}
```

## Other tools on Visionmcp (375)

- `active_learning.rollback` — Destructive — https://policylayer.com/tools/visionmcp/active-learning.rollback.md
- `artifact.reap_stale_uploads` — Destructive — https://policylayer.com/tools/visionmcp/artifact.reap-stale-uploads.md
- `active_learning.execute_retraining` — Execute — https://policylayer.com/tools/visionmcp/active-learning.execute-retraining.md
- `active_learning.plan_retraining` — Execute — https://policylayer.com/tools/visionmcp/active-learning.plan-retraining.md
- `benchmark.bootstrap_calibration` — Execute — https://policylayer.com/tools/visionmcp/benchmark.bootstrap-calibration.md
- `benchmark.bootstrap_dgx_spark` — Execute — https://policylayer.com/tools/visionmcp/benchmark.bootstrap-dgx-spark.md
- `benchmark.bootstrap_rtx_5090_fe` — Execute — https://policylayer.com/tools/visionmcp/benchmark.bootstrap-rtx-5090-fe.md
- `benchmark.refine_dgx_spark_base_foot_candidate` — Execute — https://policylayer.com/tools/visionmcp/benchmark.refine-dgx-spark-base-foot-candidate.md
- `benchmark.refine_dgx_spark_visual_candidate` — Execute — https://policylayer.com/tools/visionmcp/benchmark.refine-dgx-spark-visual-candidate.md
- `benchmark.refine_rtx_5090_fe_front_frame_candidate` — Execute — https://policylayer.com/tools/visionmcp/benchmark.refine-rtx-5090-fe-front-frame-candidate.md
- `benchmark.refine_rtx_5090_fe_visual_candidate` — Execute — https://policylayer.com/tools/visionmcp/benchmark.refine-rtx-5090-fe-visual-candidate.md
- `blender.generate_lod` — Execute — https://policylayer.com/tools/visionmcp/blender.generate-lod.md
- `blender.prepare_asset` — Execute — https://policylayer.com/tools/visionmcp/blender.prepare-asset.md
- `blender.render` — Execute — https://policylayer.com/tools/visionmcp/blender.render.md
- `camera.derive_undistorted` — Execute — https://policylayer.com/tools/visionmcp/camera.derive-undistorted.md
- `campaign.advance` — Execute — https://policylayer.com/tools/visionmcp/campaign.advance.md
- `campaign.resume` — Execute — https://policylayer.com/tools/visionmcp/campaign.resume.md
- `campaign.start` — Execute — https://policylayer.com/tools/visionmcp/campaign.start.md
- `candidate.evaluate_transaction` — Execute — https://policylayer.com/tools/visionmcp/candidate.evaluate-transaction.md
- `component.generate` — Execute — https://policylayer.com/tools/visionmcp/component.generate.md
- `coverage.acquire_missing` — Execute — https://policylayer.com/tools/visionmcp/coverage.acquire-missing.md
- `dataset.generate` — Execute — https://policylayer.com/tools/visionmcp/dataset.generate.md
- `dataset.train_feature_model` — Execute — https://policylayer.com/tools/visionmcp/dataset.train-feature-model.md
- `evidence.discover` — Execute — https://policylayer.com/tools/visionmcp/evidence.discover.md
- `geometry.run_ensemble` — Execute — https://policylayer.com/tools/visionmcp/geometry.run-ensemble.md
- `photogrammetry.run` — Execute — https://policylayer.com/tools/visionmcp/photogrammetry.run.md
- `portfolio.execute_initial` — Execute — https://policylayer.com/tools/visionmcp/portfolio.execute-initial.md
- `portfolio.execute_parametric_seed` — Execute — https://policylayer.com/tools/visionmcp/portfolio.execute-parametric-seed.md
- `recon.bootstrap` — Execute — https://policylayer.com/tools/visionmcp/recon.bootstrap.md
- `recon.continue_multiview_search` — Execute — https://policylayer.com/tools/visionmcp/recon.continue-multiview-search.md
- …and 345 more: https://policylayer.com/tools/visionmcp.md

## For agents

This record is a snapshot. Live verdicts and the full registry:

- Check every server in your MCP config at once: `npx -y policylayer stack`
- Vet a server before you add it: install the mcp-precheck skill — `npx skills add https://policylayer.com` (skill text: https://policylayer.com/skill.md)
- Query the registry over MCP: endpoint `https://api.policylayer.com/mcp` — tools `check_mcp_server`, `check_mcp_stack`, `check_tool`, `search_registry`, `get_change_events`

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Source: the PolicyLayer MCP registry — one continuously verified record per MCP server. Full record: https://policylayer.com/registry?q=visionmcp · API: https://policylayer.com/registry/api · Policy library: https://policylayer.com/policies/visionmcp