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Image, video and audio · MCP server

Editmamei: MCP server, setup and security

Editmamei is an MCP server published on GitHub that lets an AI agent plan and execute image edits using native Adobe Photoshop tools. Its repository has 15 stars and its last commit is from October 24, 2026, but it declares no licence.

Actively maintainedNo licence

What Editmamei does

According to its repository: “Natural-language interface for Adobe Photoshop that plans edits and executes them with native Photoshop tools rather than generative AI.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Editmamei is listed under Image, video and audio, a category of 67 servers in the directory, where it ranks #49 by stars.

Topics declared by the repository: adobe-photoshop, ai-photo-editing, batch-editing, claude, extendscript, photo-editing.

Installing and connecting Editmamei

Distribution modes declared in the official MCP registry:

  • npm package (Node.js, usually started with npx)

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: TypeScript. Listed systems: macOS, Windows.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

Points found for Editmamei:

  • No licence: without a licence the code is not legally reusable, even if it is public. Avoid it in a company setting without the author's agreement.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on August 5, 2026, the editmamei/editmamei repository has 15 stars and 4 forks, with 0 open issues. It has more stars than 33% of the servers in the directory. It received changes this month. Version published in the registry: 1.9.2 (October 24, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

ScreenpipeScreenpipe : 22.1K22.1KFunASRFunASR : 20.8K20.8KRemove AI WatermarksRemove AI Watermarks : 6.1K6.1KOpenScreenOpenScreen : 4.9K4.9KOpenPostOpenPost : 755755FableCutFableCut : 746746Anki MCP ServerAnki MCP Server : 531531MCP youtube transcriptMCP youtube transcript : 492492EditmameiEditmamei : 1515
GitHub stars of the most followed servers in the category (log scale); Editmamei in orange. Checked October 25, 2026.

Verdict

Editmamei is a reasonable choice; check the points below before connecting it.

Strengths

  • Active project: recent commit
  • Listed in the official MCP registry

Limitations

  • No licence declared

Avoid if…

  • Company use without the author's agreement

Frequently asked questions

How do I install Editmamei?

Editmamei is distributed as npm package (Node.js, usually started with npx). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of editmamei/editmamei.

Is Editmamei free?

The code is public but has no declared licence: it is not formally free to reuse.

Is Editmamei safe?

Points to watch: no licence. Give it minimum rights and approve sensitive actions.

Is it an official server?

Nothing says so: it is a project published by editmamei on GitHub. Check who maintains it before giving it access.

What are the alternatives to Editmamei?

In the same category: OpenScreen, Remove AI Watermarks, FunASR, and Oh My Cassette. OpenScreen and Remove AI Watermarks score higher on our grid.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score