Selvage: MCP server, setup and security

What Selvage does

According to its repository: “LLM-based code review with AST-based context extraction, supporting Claude, GPT, Gemini and other models via OpenRouter.”

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. Selvage is listed under Developer tools, a category of 475 servers in the directory, where it ranks #287 by stars.

Installing and connecting Selvage

Distribution modes declared in the official MCP registry:

• PyPI package (Python, started with uvx or pip)

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: Python.

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 Selvage:

• 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 May 30, 2025, the selvage-lab/selvage repository has 36 stars and 8 forks, with 0 open issues. It has more stars than 47% of the servers in the directory. Last change 3 months ago. Version published in the registry: 0.4.1 (February 17, 2026).

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