# vision.query

Query an observed perceptual graph with exact artifact citation.

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

## Facts

- Tool: `vision.query`
- 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.query",
    "arguments": {}
  }
}
```

## Why vision.query is rated Low

This tool queries existing data structures (a perceptual graph) and returns results with citations. No modification, deletion, or execution capabilities are indicated. The operation is non-destructive and has no side effects beyond returning information to the caller. This is a classic Read operation.

From the tool's own definition: "Tool name 'query' combined with description 'Query an observed perceptual graph' indicates data retrieval. The phrase 'exact artifact citation' suggests read-only access to return referenced data without modification."

## Use case

AI agents call vision.query 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.query": {}
  }
}
```

## 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