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SQLite Local AI Memory MCP server

by cheveguerra·io.github.cheveguerra/sqlite-local-ai-memory·v1.5.3·1 stars
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100% In-Process Bare-Metal Hybrid Memory Engine & MCP Server for LLMs (SQLite + Int8 Vectors).

B83/100grade B
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Safety scan
B83/100

full report

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Growing

1 stars961 downloads/wk

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

SQLite Local AI Memory tools (5, 1 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • consolidatewrite action

    Executes cognitive memory maintenance (AutoDream): synthesizes progress, archives obsolete notes, and updates the project dashboard (batch write). Call only at session close or after major milestones, NOT on every turn. Preserves other projects' cards. Returns triage summary report.

  • get_current_state

    Retrieves the active executive working dashboard, active project focus, and recent milestones (read-only). Use during session bootstrap or task switching for high-level orientation. Do NOT use for granular fact searches (use 'search_memory'). Returns formatted markdown dashboard.

  • get_fact_lineage

    Traces the full evolutionary history and supersede chain of a fact by its UUID (read-only). Use when auditing how or why a rule changed, or resolving conflicting facts. Obtain the UUID via 'search_memory'. Returns chronological revisions and rationale.

  • save_fact

    Persists an atomic fact, preference, or technical rule into long-term memory with automatic semantic deduplication and vector indexing (append-only write). Use for immediate logging; for search use 'search_memory', for evolution audits use 'get_fact_lineage', and for batch synthesis use 'consolidate'. Returns the assigned fact UUID and status.

  • search_memory

    Searches long-term memory using hybrid FTS5 BM25 lexical and vector cosine similarity with RRF ranking (read-only). Supports Point-in-Time queries via 'as_of'. Use for factual lookup and technical recall. For active high-level board use 'get_current_state'; for fact revisions use 'get_fact_lineage'. Returns ranked list of scored memory items.

Public scan report

scanner v0.1.10 · 2026-10-24 · same rubric, same numbers if you re-run it

no findings
  • Code scan23 source files scanned25/25
  • –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 0 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 83/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How SQLite Local AI Memory compares

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

Safety score
83/100
higher than 60% of 802 Databases servers
Tools
5
the typical Databases server has 8
Tools that change things
20%
typical: 10%. Fewer write tools means less an agent can break
GitHub stars
1
more than 45% of 602 Databases servers
Downloads a week
961
more than 90% of 328 Databases servers with a package

What its tools let an agent do: 3 read · 1 create · 1 change

Install SQLite Local AI Memory in Claude Code, Cursor or VS Code

Runs npx -y sqlite-local-ai-memory on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add sqlite-local-ai-memory -- npx -y sqlite-local-ai-memory
Add to Cursor

What the publisher says

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

🧠 SQLite Local AI Memory

Give your AI assistant a real, permanent memory in 60 seconds.

No monthly database subscriptions. No Docker setup. Just a single private file on your computer.

🛑 The Problem: Why does your AI keep forgetting?

If you use AI coding assistants or chatbots (Claude Desktop, Cursor, Antigravity, etc.), you already know the frustration:

  1. Total Amnesia: The moment you close the chat or start a new window, the AI forgets who you are, your tech stack, your server IPs, and your personal preferences.
  2. Copy-Paste Hell: You have to re-explain the same context over and over, or paste giant text files into every single prompt.
  3. Wasted Money & Sluggish Chats: Shoving massive chat histories into every prompt burns through your token budget, costs real money, and makes the AI slower and prone to confusion.

✨ The Solution: A Private Brain in a Single File

sqlite-local-ai-memory gives your AI assistant a permanent, organized brain stored safely in a single file (memoria.db) right on your own machine.

How it works (In Plain English):

Keeps track of your immediate focus: active tasks, decisions made today, and next steps. When you open a fresh chat tomorrow, your AI instantly knows where you left off.

  • 📝 1. The Active Notepad (What we are doing right now):

Stores concrete knowledge—like your server configurations, preferred coding styles, or family rules. When something changes (e.g., an IP changes), it updates the active fact while keeping an audit trail of the past.

  • 📚 2. The Knowledge Vault (Facts that rarely change):

Just like the human brain organizes thoughts during sleep, when your AI is idle, it quietly reviews raw notes, merges duplicates, and connects related facts into a clean summary.

  • 🌙 3. Nightly Cleanup / AutoDream (Keeping the brain tidy):

⚡ What Makes This Unique? (The "Secret Sauce")

Unlike simple chat logs or generic vector databases that dump raw text into a black box, this system uses 6 smart cognitive mechanisms that make your AI truly understand its memory:

🌙 1. AutoDream Engine (Sleep-Cycle Memory Cleanup)

Instead of letting thousands of chat messages pile up into an unreadable mess, AutoDream acts like the human brain during REM sleep:

  • Live Dashboard: Keeps an active summary of what you are building today.
  • Permanent Knowledge: Automatically distills key technical decisions into compact facts in SQLite.
  • Never Loses Unfinished Work: If a problem is left open or unresolved, AutoDream safely archives it with an [UNRESOLVED_CASE] tag so your AI can resume debugging weeks later without losing historical clues.

🐣 2. Open Case Incubator & Dynamic Memory Window

When troubleshooting a complex bug over multiple days, active investigations stay safely in an "incubator". When the AI finally consolidates the case, it doesn't just read the last message—it dynamically rewinds back in time to the exact moment the issue started, giving the AI 100% of the historical context to write the permanent fix.

⚖️ 3. Real-Time Contradiction Arbiter (Curing AI "Time Blindness")

Standard vector databases are completely blind to time. If you tell an AI "My server IP is .100" and two weeks later say "We moved the server to .205", normal vector search returns both and the AI hallucinates. Our Semantic Arbiter detects state contradictions instantly: it archives the old IP and sets the new IP as active in real time.

🚀 4. 100% Embedded Storage (Zero Database Servers)

Zero Docker containers to maintain. You don't need to install Chroma, run PostgreSQL with pgvector, or pay for cloud databases like Pinecone. Everything—keyword indexing and vector math—lives inside a single local SQLite file. It retrieves active notes in under 0.1 ms and deep memories in under 1.5 ms.

Shortened. The full README is on GitHub.

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

SQLite Local AI Memory: common questions

Is SQLite Local AI Memory MCP server safe?
Mostly: it is graded B (83/100). Read the SQLite Local AI Memory safety report
How do I install SQLite Local AI Memory?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does SQLite Local AI Memory need an API key?
Yes. The registry entry asks for GEMINI_API_KEY.
Is SQLite Local AI Memory maintained?
The last commit was 11 days ago (2026-10-24). The latest release is v1.5.3.
What can I use instead of SQLite Local AI Memory?
Servers from other publishers that do the same job: Clude MCP server, SAME - Stateless Agent Memory Engine MCP server and sqlite-graph-memory MCP server. Compare all SQLite Local AI Memory alternatives.
How does SQLite Local AI Memory compare with other Databases MCP servers?
safety score 83/100 (higher than 60% of 802 Databases servers); tools 5 (the typical Databases server has 8); tools that change things 20% (typical: 10%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to SQLite Local AI Memory

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

All SQLite Local AI Memory alternatives →
  • Clude
    Portable agent memory anchored on Solana. Local SQLite + vector recall, open export.
    B
  • SAME - Stateless Agent Memory Engine
    Persistent memory for AI coding agents. Local-first SQLite + vector search. 17 MCP tools.
    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