Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/putervision/state-memory-mcp/vision-memory-mcpgit clone --depth 1 https://github.com/putervision/state-memory-mcpWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00875 | $0.00875 |
| Opus 5 | $0.00438 | $0.00438 |
| Sonnet 5 | $0.00175 | $0.00175 |
| Haiku 4.5 | $0.00088 | $0.00088 |
Grade B, and why
vision-memory-mcp scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
* **Google Antigravity (`~/.gemini/config/config.json`)**: Add these rules to your `"globalPermissionGrants"` -> `"allow"` list: Copies of this mod
2 near-identical copies found in the catalogue:
- vision-memory-mcp — 100% identical, 0 lines differ
- vision-memory-mcp — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual Memory (vision-memory-mcp)
This project utilizes vision-memory-mcp to cache visual states, record layout transitions, provide element grounding, and avoid repetitive LLM vision calls.
1. Mandatory Workflow & Priority
- Orient: Call
get_session_contextto align your visual state context at the start of work. - Search: Call
recall_memory(text/image search) before recreating duplicate UI state paths. - Ingest/Verify: ALWAYS call
analyze_screenshotbefore querying any front-end vision models.- Cache Hit (
is_known: true): Do NOT use vision models; read the returneddescriptionas context and usegrounded_elements(selectors, coordinates) for action target selection. - Cache Miss (
is_known: false): Query your vision model, then runanalyze_screenshotwith both the image and description to seed the cache.
- Cache Hit (
- Action Target Execution: Use
predict_next_actionto retrievegrounded_targethandles (target_selector,target_coords) for deterministic UI clicks and typing. - Transitions: Call
record_outcomeafter every click/type/scroll action to construct navigation paths. - Privacy & Cleanup: Call
forget_stateto purge sensitive or secret states from storage.
2. Tool Reference Summary (15 Core MCP Tools)
analyze_screenshot: Ingest screenshot(s) (single or batch viaitems), lookup cache, return layout description and grounded elements.recall_memory: Search visual memory by description query or base64 image query (read-only).record_outcome: Save UI action execution outcomes, transitions, or log visual blockers (action_type: 'blocker').get_navigation_paths: Find path between states using BFS navigation graph.predict_next_action: Predict best next UI action and target coordinates based on transition success rates and AX tree grounding.compare_states: Compare visual states structurally (has_layout_change) or compare video recordings (video_a_id/video_b_id).get_session_context: Fetch aggregated visual context, recent/frequent states, transitions, cache hit ratios, token savings metrics, and server version info.manage_snapshot: Unified snapshot management (save,diff,export,restore) for visual checkpoints and regression detection.manage_visual_spec: Visual SDD design contract baseline registration (set), live verification (verify), and listing (list).manage_video: Unified video memory operations for ingestion (ingest), semantic search (search), and keyframe timelines (timeline).create_evidence_pack: Create cryptographic, multi-modal evidence pack linking video keyframes, state graph tasks, and visual proof.export_trajectories: Export multimodal visual transitions and joint workflow trajectories (json,llava,qwen2_vl,joint).undo_visual_mutation: Revert accidental state or transition edge ingestions.forget_state: Purge a specific state and vector embedding from storage for privacy.wait_for_visual_state: Poll for target visual state until present or timeout occurs.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 42 lines · 875 tokens per session scan B 64a612948bea
vision-memory-mcp is a cursor rule published in the GitHub repository putervision/state-memory-mcp (80 stars, last pushed 13d ago), licensed MIT. It adds 875 tokens to every session, about $0.0044 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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