Tokenectomy is an open-source MCP server for machine-to-machine AI agent workflows. It removes framework noise and redacts secrets from error logs before returning them to agent context windows, with Cargo and Docker installation options.
In the AI security & guardrails space, Tokenectomy takes a focused approach. It focuses on preventing noisy or secret-containing AI agent error logs from consuming context windows or exposing sensitive data. Tokenectomy is an open-source project aimed at AI agent developers and platform engineers. The project is open source (Open Source). Tokenectomy is available on the web, the command line, and API, and it can be self-hosted.
daffa2555 builds and maintains Tokenectomy. Among its 7 catalogued features are error sanitization, secret redaction, and framework filtering. It exposes integrations via an MCP server.
Summary written by a language model from the project’s public pages.
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