I built a way to stop massive tool outputs from blowing up AI agent context windows

Hey everyone. I have been building LeanCTX to manage context for coding agents. Up until now, it was mostly focused on the file system, deciding what your agent reads and compressing it. With the latest update, I shifted the architecture to solve a different problem: bloated tool outputs. When you give an agent access to external tools, the raw data they return often burns through your token budget and degrades the agent's reasoning. To fix this, LeanCTX now acts as a gateway for the ecosystem. You can plug in external tools using a single command, like lean-ctx addon add repomix. If it speaks MCP, it fits seamlessly. Instead of just passing the raw output to the model, the gateway intercepts it. It treats all addon output as untrusted and scrubs it for secrets. It then compresses the response to fit a specific token budget. If a tool returns a massive data dump, the system spills the oversized results to disk and hands the model a small reference handle instead. Everything is indexed in the background so the agent can search for it later. Tools are no longer isolated side channels. They become a native part of the managed context. I put together a registry with 19 tools so far, covering things from memory to reasoning. I included projects like Headroom, Serena, Repomix, and Mem0. A fragmented ecosystem helps no one, so the goal is to integrate rather than compete. Ten of them install with one command, and for four of them, LeanCTX handles the binary installation entirely.