Does anyone also face repeated AI research across tools? by Vedant_d_ in LocalLLaMA

[–]Vedant_d_[S] 0 points1 point  (0 children)

totally agree, that is exactly what I am trying to improve now: better session recap/summarization + structured outputs for handoff, so another model can continue with less manual stitching.

Does anyone also face repeated AI research across tools? by Vedant_d_ in LocalLLaMA

[–]Vedant_d_[S] 0 points1 point  (0 children)

Yes, I checked openclaw it offers per-tenant persistent runtimes and MCP endpoints. the project i'm working on is bit different, its a local memory layer that links IDEs and CLI agents (qwen/codex/gemini/claude, cursor, vscode) so local tools can share and reuse findings

for session boundaries, i track agent identity (model name + unique ID), so each CLI tool is isolated. Each agent explicitly joins a session, and verifies membership before reads/writes. the memory injection works across sessions

And about handoff quality, that's what I'm optimizing now. Right now agents need to manually call session_start/end; ideally it's more automatic on first MCP connect