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memo-mcp operator guide

This guide is for the people who install, configure, tune and run memo-mcp. It is written for readers comfortable with a terminal, SQLite, environment variables and Prometheus.

memo-mcp is a single, pure-Go binary. It exposes a knowledge base to AI agents over the Model Context Protocol (MCP) on stdio. It stores everything in one SQLite file per knowledge base, and it ships with a CLI and a read-only web UI over the same store. There is no daemon to deploy, no external database and no network dependency after a one-time model download.

What you will find here

PartRead it when you need to…
I. How it worksUnderstand the processes, the data model, the search pipeline and the security boundaries
II. Install and deployInstall, connect MCP clients, lay out several knowledge bases, upgrade, run offline
III. Configuration referenceLook up an environment variable, a command, a flag, the overrides file or a path on disk
IV. Retrieval tuningChange ranking, switch embedding models, try the reranker, and measure whether a change helped
V. Knowledge lifecycleAdminister ingest, facts, trust, the graph index, compaction and deletion
VI. Monitoring and observabilityScrape metrics, write alerts, read logs, use the call log
VII. OperationsBack up, verify, size, export, troubleshoot, release

Conventions

  • Commands are shown as memo-mcp <command>. Every command reads the same environment (MEMO_HOME, MEMO_KB, …), so set it the same way the MCP client does.
  • “Knowledge base” (KB) means one SQLite file. A “namespace” is a label inside one file.
  • Addresses such as memo://chunk/42 identify records; every CLI command and the UI accept them.
  • Defaults quoted here are the shipped values for v1.4. memo-mcp profiles show and memo-mcp --help print the live values for your build.

Deeper references

This guide states what to do and what it costs. The design documents explain why:

  • Architecture: the 1.x contract, formulas and defaults.
  • Schema: every table and column, trust transitions, time rules.
  • Eval reports: measured quality and cost per release.

Looking for the non-technical introduction? See the user guide.