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Engraphy MCP server

by devon-clarkk·io.github.devon-clarkk/engraphy·v0.3.0·1 stars

Self-hosted MCP memory server: a typed knowledge graph on Postgres 16 and pgvector.

B73/100grade B
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Safety scan
B73/100

full report

Adoption
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1 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

Engraphy tools

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

Public scan report

scanner v0.1.10 · 2026-10-02 · same rubric, same numbers if you re-run it

no findings
  • –Code scanpackage could not be scannedn/a
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 1 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 73/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Engraphy compares

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

Safety score
73/100
higher than 32% of 802 Databases servers
GitHub stars
1
more than 45% of 602 Databases servers

Install Engraphy in Claude Code, Cursor or VS Code

claude mcp add engraphy -- docker run -i --rm ghcr.io/devon-clarkk/engraphy:0.3.0
Add to Cursor

What the publisher says

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

Engraphy

An MCP server giving AI agents associative memory, modelled on the human mind.

Quickstart · Documentation · Tool reference · Design set · Contributing

The name comes from engraphy, an old term from memory science for the process of laying down an engram, the trace a memory leaves in the brain. Engraphy does that for agents: it checks each new memory against what it already knows before the write lands, merging restatements, linking genuinely new facts, and never silently overwriting. Nothing is deleted, so history stays walkable.

Engraphy is self-hosted. It stores what an agent learns as a typed knowledge graph on Postgres + pgvector: writes deduplicate themselves against existing memory, retrieval fuses semantic and lexical search, isolation between users is enforced by the database, and the whole shape of memory is declared per application as a pack.

It exists to replace the reference MCP memory server's flat-JSON, single-user, stdio model with something that survives concurrency, paraphrase, duplicates, and years of accumulated memory. It speaks the Model Context Protocol, so any MCP client (a VS Code extension, a desktop app, another agent) can use it over HTTP.

Source-available. Licensed under the Business Source License 1.1: read it,

run it, build on it, and use it in production for your own product. Offering

Engraphy itself as a hosted or managed service to third parties is reserved to

the Licensor until the Change Date, when it converts to Apache-2.0. See

License.

What it does

Shortened. The full README is on GitHub.

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

Engraphy: common questions

Is Engraphy MCP server safe?
Mostly: it is graded B (73/100). Read the Engraphy safety report
How do I install Engraphy?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Engraphy need an API key?
Yes. The registry entry asks for ENGRAPHY_DATABASE_URL.
Is Engraphy maintained?
The last commit was 33 days ago (2026-10-01). The latest release is v0.3.0.
What can I use instead of Engraphy?
Servers from other publishers that do the same job: Local Memory MCP server, Memory Vault MCP server and CogniCore MCP server.
How does Engraphy compare with other Databases MCP servers?
safety score 73/100 (higher than 32% of 802 Databases servers); github stars 1 (more than 45% of 602 Databases servers). Full comparison.

Alternatives to Engraphy

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

  • Local Memory
    Persistent local AI memory. SQLite + FTS5 + vector search, knowledge graph. No cloud, no API keys.
    A
  • Memory Vault
    Local-first AI memory layer with hybrid search. Postgres + pgvector. Self-hosted, MIT.
    B
  • CogniCore
    Memory, reflection and safety for AI agents. Hosted or local, no vector database.
    A
  • GeoLens
    Read-only access to a self-hosted GeoLens spatial catalog: datasets, features, maps, sandboxed SQL.
    B
  • sqlite-graph-memory
    Recall over your markdown notes: vector search plus your [[wikilinks]] as a graph, in SQLite.
    A