QueryWeaver: MCP server, setup and security

What QueryWeaver does

According to its repository: “An MCP server for Text2SQL: transforms natural language into SQL using graph schema understanding.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. QueryWeaver is listed under Databases, a category of 138 servers in the directory, where it ranks #16 by stars.

Topics declared by the repository: falkordb, semantic-layer, text2sql.

Installing and connecting QueryWeaver

Distribution modes declared in the official MCP registry:

• Docker (OCI) image

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: Python.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to QueryWeaver. That does not replace reading the code.

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 July 27, 2025, the FalkorDB/QueryWeaver repository has 1,086 stars and 137 forks, with 38 open issues. It has more stars than 92% of the servers in the directory. It received changes this month. Version published in the registry: 0.0.11 (September 11, 2025).

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