memory-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@memory-mcpRemember that I prefer updates with bullet points."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
memory-mcp
A standalone MCP server for persistent agent memory — short/long-term tiers, measurable reliability, and lifecycle maintenance — backed by SQLite (FTS5 + sqlite-vec) with local MiniLM embeddings. No external services, no API keys.
Requirements
Node.js >= 22
The package ships compiled JavaScript, so no TypeScript toolchain is needed at runtime.
Related MCP server: MCP Vector Memory
Install
npm install @jommar/memory-mcpTwo executables are provided:
Command | Purpose |
| The MCP server (stdio by default, HTTP via |
| Store maintenance CLI ( |
Quickstart
stdio (default)
Point your MCP client at the server binary:
{
"mcpServers": {
"memory": {
"command": "memory-mcp-server"
}
}
}Or run it directly:
memory-mcp-serverWith npx, select the server bin explicitly (installs the package on first use):
npx -y -p @jommar/memory-mcp memory-mcp-serverHTTP (localhost only)
MEMORY_TRANSPORT=http memory-mcp-serverThe HTTP endpoint binds to 127.0.0.1:3000 by default and serves both the modern
(2026-07-28) and legacy (2025-11-25) protocol revisions from the same endpoint, so
any MCP client can connect. The server is stateless — no session id is required.
First run
The store is created automatically at ~/.memory-mcp/memory.db. Embeddings are
offline-first: no model is downloaded unless you opt in.
# opt in to the one-time model download (about 23 MB, MiniLM-L6, q8 quantized)
MEMORY_EMBEDDING_OFFLINE=false memory-mcp-serverUntil a model is available, remember and recall still work — they fall back to
keyword search only. Use the CLI reindex to backfill vectors after the model is
in place.
Configuration
All configuration is via MEMORY_* environment variables (no config file):
Variable | Default | Purpose |
|
| SQLite database file |
|
|
|
|
| HTTP bind host (localhost only) |
|
| HTTP bind port |
|
|
|
|
| Timeout for a model download attempt |
|
| Where downloaded models are cached |
|
| Explorer UI port (dev tool; auto-increments when busy) |
Tools
Ten tools are registered: remember, recall, get, update, forget, list,
confirm, contradict, promote, consolidate. See docs/tools.md
for the full reference with inputs and behaviors.
remember accepts an interactive opt-in: when it finds near-duplicate entries it
can ask the client to merge or create (MRTR), and degrades gracefully for clients
without interactive support.
Maintenance CLI
memory-mcp export ./out # write every memory as a markdown frontmatter file
memory-mcp import ./staging # validate, then import (never overwrites existing keys)
memory-mcp reindex # rebuild FTS + vector indexes from stored content
memory-mcp stats # print store countsMemory explorer (UI)
A read-only visual explorer for the store: links graph (React Flow, force-directed
layout clustered by type), reliability breakdown per memory, history, supersession
chains, filters by scope/type/tier/status, and a maintenance drawer listing
consolidate proposals (orphans, stale entries, duplicate clusters) with
click-to-select. It opens the SQLite database read-only, so it is safe
to run alongside a live server and cannot mutate data.
The UI lives in the ui/ workspace and is a development tool — it is not part of
the published package:
npm run ui:build # compile the API server + bundle the frontend
npm run ui:start # serve at http://127.0.0.1:3001For frontend development with hot reload: npm run ui:dev in one terminal
(proxies /api to 3001) and npm run ui:start in another.
If the port is taken, the server auto-increments (3001 → 3010) and prints the
bound URL. Configuration: MEMORY_DB_PATH (same store as the server) and
MEMORY_UI_PORT (default 3001). The bind host is always 127.0.0.1.
Documentation
docs/tools.md — tool reference
docs/reliability.md — reliability model and lifecycle rules (the report-only maintenance engine behind
consolidate)
License
MIT — see LICENSE.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Persistent memory and knowledge management for AI agents with semantic search and 50+ tools.
Persistent memory for AI agents: add, search, update, and delete long-term memories.
Persistent memory for AI agents. Search, store, and recall across sessions.
Persistent memory for AI agents. Search and store durable facts, preferences and decisions.
Related MCP Servers
- -licenseNot gradedqualityNot gradedmaintenanceProvides persistent local memory functionality for AI assistants, enabling them to store, retrieve, and search contextual information across conversations with SQLite-based full-text search. All data stays private on your machine while dramatically improving context retention and personalized assistance.3
- AlicenseNot gradedqualityNot gradedmaintenanceProvides AI coding agents with persistent, long-term memory through local semantic search and SQLite storage. It enables agents to save and retrieve architectural decisions or project context across different conversation sessions without requiring cloud services.
- FlicenseNot gradedqualityDmaintenanceProvides persistent AI agent memory using a local vector database for long-term semantic storage and short-term session scratchpads. It enables low-latency memory operations including search, storage, and bulk management without external cloud dependencies.
- AlicenseNot gradedqualityCmaintenanceProvides persistent long-term memory for LLMs via local SQLite storage and semantic search, enabling recall across sessions without external APIs.194MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/jommar/memory-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server