TOMC Memory runs on your own machine — the client starts it, so there is no endpoint to ping. Last commit 6 Nov 2026.
CPU task-specific context preparation and explicitly saved local project notes through MCP.
We read the source, 1 h ago · rules 995398eba69f
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
proc = subprocess.run(
update = chain["updates"].prepare(history, task)
delivery_id = "d-" + uuid.uuid4().hex[:16]
env = dict(os.environ)
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
Local DevDocs MCP Server (Developer Docs with project specific context awareness)
Persistent memory layer that saves and recalls your project context and preferences.
Bring your saved preferences, project decisions, and useful context into your next AI conversation.
Local-first agent memory with verified backup rotation and explicit project isolation.
Local memory and context retrieval for AI agents through CueMap.
Local deterministic project memory for AI agents with context packs, gates and checkpoints.
Shared memory for your AI tools: tasks, notes and context every tool can read and write over MCP.
Project memory, tasks and Telegram notifications for your coding agent. Chip account required.
Answers built from our own checks of this server.