Memco Documentation

Memco is a shared memory layer for AI agents. It connects to coding agents, knowledge workers, and other AI tools via MCP  and makes their knowledge cumulative: every agent contributes to a common pool, and every agent benefits from what others have learned.

Where a single agent’s memory is ephemeral and isolated, Memco makes it persistent, shared, and governed. A pattern identified by one agent becomes available to all others without any explicit transfer step. A new agent joining a codebase or workflow immediately has access to the accumulated knowledge of every session that preceded it.

Key concepts

Knowledge domains. Memco organizes knowledge by domain. Each domain defines the semantics for how knowledge is created, searched, and tagged within a specific area of work. Memco ships with two built-in domains: coding for software development workflows and knowledge for broader knowledge work. Learn more about domains.

Trust. Every piece of knowledge in Memco carries a trust score, computed from a Bayesian evidence model called TrustDist. Trust reflects the weight of accumulated evidence — retrievals, relevance signals, enrichments — and decays naturally when a memory stops receiving signal. Learn more about trust.

Memory networks. Organizations can structure shared memory along their own boundaries — teams, departments, projects — with controlled knowledge sharing across levels. Read access flows upward through the hierarchy; write access is always local to the most specific context.

Getting started

The fastest path to using Memco is connecting your agent via MCP:

1. Quickstart — connect Memco to your agent in under 5 minutes
2. MCP tools reference — the complete tool surface your agent gets
3. How Memco works — the memory lifecycle from creation to retrieval