MemDrive
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., "@MemDrivewhat do you remember about the acme project?"
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.
MemDrive
Shareable memory for AI coding agents. Teach Claude Code (or Cursor) something once, then carry that knowledge across sessions — and hand it to a teammate as a single file they can import into their agent.
I taught Claude Code something on my laptop, exported a pack, my friend
imported it in Cursor, and their agent knew it.MemDrive is a tiny MCP server + CLI. No
cloud, no account, no embeddings service — just a local SQLite database and
plain-text .jsonl packs you own.
Install
npx memdrive@latest installThis wires MemDrive into every agent it finds:
Claude Code — adds the MCP server and (optionally) a Stop hook that auto-distills durable memories when a session ends.
Cursor — adds the MCP server (you call
remember/recallyourself).
It backs up each config before touching it, never clobbers your other MCP servers, and prints exactly what changed. Then open your agent and ask: "what do you remember?"
Remove it any time:
npx memdrive@latest install --removeRelated MCP server: mindkeg-mcp
The three tools
Your agent gets three tools it can call on its own:
Tool | When it fires |
| You decide something, state a rule/preference, or hit a gotcha and its fix. Stores a short, distilled memory — never a transcript. |
| At the start of a task. Returns the most relevant memories, pinned first, inside labelled |
| A memory is wrong or outdated. Tombstones it by id. |
Memories have a type (decision, convention, gotcha, preference,
fact, snippet, todo_context), an optional project scope, and tags.
Sharing packs
Packs are the whole point. A pack is one .jsonl file — a header line plus one
memory per line.
# Export the acme project's memories (personal preferences are left out)
memdrive export acme.jsonl --project acme
# On another machine / in another agent
memdrive import acme.jsonl --name acme-teamIdempotent. Every memory has a ULID, so re-importing an updated pack only adds the new entries. Share the file over GitHub or Drive and re-import whenever it changes — that's your sync story for v0.1.
Secret-safe. Export scans for API keys, tokens, JWTs, connection strings, and private keys, and refuses (naming each finding) unless you pass
--force.Provenance kept. Imported memories are labelled
source=pack:<name>and are never auto-pinned into your context.
Other commands
memdrive list [--project x] [--all] # see what's stored
memdrive status # DB path + counts by type/source
memdrive serve # run the MCP server (your agent does this)Everything lives in ~/.memdrive/local.db. Override with MEMDRIVE_DB for
scratch/testing.
Security note
Imported packs are untrusted text. A pack is just JSON someone else wrote —
read the .jsonl before importing it, exactly as you would a shell script from
the internet. MemDrive relabels provenance and refuses to pin imported memories,
but it cannot vouch for their content.
How it works
Storage: SQLite with an FTS5 full-text index. Search is
bm25relevance, pinned-first, with a recency tiebreak; tombstoned and expired memories are never returned.Server: stdio MCP.
recallrenders memories under a token budget so it never blows up your context.Distill hook: on Claude Code session end, MemDrive tails the transcript and asks a headless
claude -pto extract ≤5 durable memories as strict JSON, validates them, redacts secrets, and stores them withconfidence=0.6.
Roadmap
v0.1 is deliberately small. Next up, roughly in order:
Embeddings (hybrid FTS + vector search) behind the same
recallcontractCollections for grouping memories beyond
project/tagsLive mounts / sync and an HTTP transport
Review queue for triaging imported packs
More clients (Windsurf, Cline, VS Code)
The v0.1 interfaces — the store API, the recall contract, and the JSONL pack
format — were chosen to survive all of the above without a migration.
Develop
npm install
npm run build # tsup → dist/cli.js
npm test # vitest
npm run typecheckMIT licensed.
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 Servers
- AlicenseAqualityAmaintenancePersistent shared memory for AI coding agents. Stores facts as entity/key/value triples with hybrid semantic search, task checkpoints, and conflict resolution — shared across Claude Code, Codex CLI, and GitHub Copilot.Last updated162355AGPL 3.0
- Alicense-qualityCmaintenanceHelps AI coding agents remember what they learn across sessions by storing and retrieving atomic learnings, enabling persistent memory for AI tools.Last updated321MIT
- Alicense-qualityDmaintenanceProvides long-term memory for AI coding agents, enabling them to remember, search, and organize information across sessions and platforms like Claude Code, ChatGPT, and Cursor.Last updated187MIT
- Alicense-qualityAmaintenancePersistent shared memory for AI coding agents that turns a folder of markdown files into searchable memory across sessions, repos, and machines.Last updated41Functional Source , Version 1.1, MIT Future
Related MCP Connectors
Persistent memory for AI agents. Search, store, and recall across sessions.
Universal memory for AI agents and tools. Save, organize and search context anywhere.
Persistent memory for AI agents — verbatim conversations, searchable by meaning.
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/shaantanu314/memdrive'
If you have feedback or need assistance with the MCP directory API, please join our Discord server