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Memory Find MCP server

by kKEo·io.github.kKEo/memory-find·v1.5.0
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Local, explainable knowledge base for AI agents: hybrid search with provenance over SQLite.

A88/100grade A
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If you have run it, two minutes of your experience saves the next person an afternoon.

Memory Find tools

No tool declarations could be read from the package source. They show once the server is installed.

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How Memory Find compares

Against every graded Databases MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
88/100
higher than 75% of 802 Databases servers

Release history: 2 versions in the registry since 2026-10-03, latest 2026-10-09, typically one every 5 days.

Install Memory Find in Claude Code, Cursor or VS Code

The registry entry has no remote endpoint or installable package.

What the publisher says

From the Memory Find repository's README, as published. We do not edit it. Read it on GitHub

<!-- mcp-name: io.github.kKEo/memory-find -->

memo-mcp

A local MCP server that gives agents a measurable, explainable knowledge base: one Go binary, no cloud, no CGo, one SQLite file per knowledge base. Documents and facts go in with provenance; searches come back as one ranked list from four retrieval arms, each result with its address, trust and a reason for its rank. A human reads the same knowledge base from the terminal or as exported markdown.

It began as a Go rewrite of obra/private-journal-mcp and was rebuilt from scratch as a knowledge base in 2026-10. Version 1.0 fixes the contract: tool names and parameters, the memo:// addresses, the explain fields and the export format. How search decides is written down in docs/architecture.md; the plan for the research layers (graph, compaction, web UI) is docs/roadmap.md; the research behind it is docs/knowledge-base-sota.md.

What it does

Claude (or any MCP client) gets ten tools over one knowledge base:

For a human there is memo-mcp ui: a read-only web page on loopback with the same search (and the same explain table the agent gets), documents and passages with provenance and history, the facts timeline, entity neighbourhoods, agent-written pages, status, lint and the query log. Nothing on it can change the knowledge base.

The same addresses are readable as MCP resources (memo://doc/{id}, memo://chunk/{id}, memo://source/{id}, memo://fact/{id}), and memo://index or memo://ns/{namespace}/index give a one-line-per-document view under 8 KB for the start of a session. SKILL.md tells an agent how to use the tools well; memo-mcp export --index prints the same index for an AGENTS.md or CLAUDE.md file.

Everything is stored locally. There is exactly one outbound network call in the whole system: downloading the embedding model from Hugging Face on first start. After that, nothing leaves the machine. The server never fetches URLs; the agent fetches and passes the text.

How search works

search runs up to three retrieval arms over the same pre-filtered set of live passages and fuses them:

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Memory Find: common questions

Is Memory Find MCP server safe?
Yes, by our scan: it is graded A (88/100). Read the Memory Find safety report
Does Memory Find need an API key?
No secret keys are declared. It reads 3 settings from the environment.
Is Memory Find maintained?
The last commit was 32 days ago (2026-10-03). The latest release is v1.5.0.
What can I use instead of Memory Find?
Servers from other publishers that do the same job: Titen Memory MCP server, sqlite-graph-memory MCP server and Tinycontext MCP server.

Alternatives to Memory Find

Same job from other publishers: the closest match first, then the best rated.

  • Titen Memory
    Evidence-grounded agent memory with mandatory provenance, on local SQLite or Cloudflare D1
    B
  • sqlite-graph-memory
    Recall over your markdown notes: vector search plus your [[wikilinks]] as a graph, in SQLite.
    A
  • Tinycontext
    Token-light local memory with SQLite hybrid retrieval for MCP agents.
    B
  • Local Memory
    Persistent local AI memory. SQLite + FTS5 + vector search, knowledge graph. No cloud, no API keys.
    A
  • Remem
    Local-first automatic memory for Claude Code and Codex: capture, distill, recall from SQLite.
    B