# mcp Persistent memory for visual work: a photo gets analyzed once, then every later lookup on it is free. Useful when an agent reads the same image twice. - MCP server · `type=mcp` · Claude Code, Codex, Cursor, GitHub Copilot, Windsurf (Devin Desktop), Cline, Zed, Gemini CLI · ★ 1 - Author: phototology-ai - License: MIT · policy=link-only · description only; the file stays with the author - Source: https://github.com/phototology-ai/phototology/tree/HEAD/packages/mcp - Updated: 2026-10-18 - HTML: https://affpapa.org/en/nevibecode/mcp/phototology-ai-mcp ## What it does This MCP server from Phototology wires an agent into an image registry. The first pass over a photo bills 1 credit per lens; after that the stored result comes back at no cost, because entries are keyed by perceptual hash and sha256. It starts with `npx -y @phototology/mcp` and speaks stdio. Seven tools ship inside. `lookup_photo` tells you whether an image is already known, `analyze_photo` handles a single file, `analyze_batch` takes 1 to 200 at a time, and `enrich_photo` writes the findings into EXIF, IPTC and XMP. Three free helpers round it out: `list_lenses`, `get_credits`, `purchase_credits`. Run `analyze_batch` with `dryRun: true` first if you want the price before committing. No `PHOTOTOLOGY_API_KEY`, no server — every analyze call reaches the hosted Phototology API, and there is no local model to fall back on. Identity matching is out of scope: the `people` lens counts heads and notes physical traits, it does not match faces. C2PA signing is missing too, so `formats: ["c2pa"]` gets rejected. ## Requirements - Needs: Node.js (commands run via npx) - Environment variables: `PHOTOTOLOGY_API_KEY`, `PHOTOTOLOGY_BASE_URL`, `PHOTOTOLOGY_MCP_NO_TELEMETRY`, `DO_NOT_TRACK`, `PHOTOTOLOGY_MCP_ALLOWED_DIRS` — keys and tokens: ask the human for the values, never commit them or put them in shared files. ## Install ### Claude Code (native platform) **Platform CLI** ```bash claude mcp add --env PHOTOTOLOGY_API_KEY= --env PHOTOTOLOGY_BASE_URL= --env PHOTOTOLOGY_MCP_NO_TELEMETRY= --env DO_NOT_TRACK= --env PHOTOTOLOGY_MCP_ALLOWED_DIRS= --transport stdio mcp -- npx -y @phototology/mcp ``` Replace <…> with your own values ### Codex **Platform CLI** ```bash codex mcp add mcp --env PHOTOTOLOGY_API_KEY= --env PHOTOTOLOGY_BASE_URL= --env PHOTOTOLOGY_MCP_NO_TELEMETRY= --env DO_NOT_TRACK= --env PHOTOTOLOGY_MCP_ALLOWED_DIRS= -- npx -y @phototology/mcp ``` Replace <…> with your own values ### Cursor **Config file** File `.cursor/mcp.json`: ```json { "mcpServers": { "mcp": { "command": "npx", "args": [ "-y", "@phototology/mcp" ], "env": { "PHOTOTOLOGY_API_KEY": "", "PHOTOTOLOGY_BASE_URL": "", "PHOTOTOLOGY_MCP_NO_TELEMETRY": "", "DO_NOT_TRACK": "", "PHOTOTOLOGY_MCP_ALLOWED_DIRS": "" } } } } ``` Replace <…> with your own values ### GitHub Copilot **Config file** File `.vscode/mcp.json`: ```json { "servers": { "mcp": { "type": "stdio", "command": "npx", "args": [ "-y", "@phototology/mcp" ], "env": { "PHOTOTOLOGY_API_KEY": "", "PHOTOTOLOGY_BASE_URL": "", "PHOTOTOLOGY_MCP_NO_TELEMETRY": "", "DO_NOT_TRACK": "", "PHOTOTOLOGY_MCP_ALLOWED_DIRS": "" } } } } ``` Replace <…> with your own values ### Gemini CLI **Platform CLI** ```bash gemini mcp add -e PHOTOTOLOGY_API_KEY= -e PHOTOTOLOGY_BASE_URL= -e PHOTOTOLOGY_MCP_NO_TELEMETRY= -e DO_NOT_TRACK= -e PHOTOTOLOGY_MCP_ALLOWED_DIRS= mcp npx -y @phototology/mcp ``` Replace <…> with your own values ## When to use it - reuse one photo analysis across agent calls - price a batch before spending credits - bake structured fields into a file's metadata - spot near-duplicate images by perceptual hash - get dates, text and location off a photo as JSON ## Example prompts - Check `lookup_photo` for this image before spending anything on it - Run `analyze_batch` with `dryRun: true` over the folder and tell me the cost - Write the analysis into the EXIF of `photo.jpg` with `enrich_photo` ## Similar - [vision-analysis](https://affpapa.org/en/nevibecode/skills/vision-analysis.md) — skill · 2700 installs - [gemini-image](https://affpapa.org/en/nevibecode/skills/gemini-image.md) — skill · 1200 installs - [modlens](https://affpapa.org/en/nevibecode/skills/modlens.md) — skill · 923 installs - [minimax-image-understanding](https://affpapa.org/en/nevibecode/skills/minimax-image-understanding.md) — skill · 556 installs - [three.ws Vision](https://affpapa.org/en/nevibecode/mcp/threews-vision.md) — MCP server · ★ 250 - [VLM](https://affpapa.org/en/nevibecode/skills/vlm.md) — skill · 343 installs ## Other versions with the same name - [mcp · kubeshark](https://affpapa.org/en/nevibecode/mcp/kubeshark-mcp.md) — ★ 12110 - [mcp · butterbase-ai](https://affpapa.org/en/nevibecode/mcp/butterbase-ai-mcp.md) — ★ 3031 - [mcp · medplum](https://affpapa.org/en/nevibecode/mcp/mcp.md) — ★ 2766 - [mcp · sceneview](https://affpapa.org/en/nevibecode/mcp/sceneview-mcp.md) — ★ 1349 - [mcp · buoy-gg](https://affpapa.org/en/nevibecode/mcp/buoy-gg-mcp.md) — ★ 691 --- NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md