The memory layer for Cursor, Claude, and any AI agent

Make your AI agents

remember your work

Stop re-explaining your codebase, your preferences, and yesterday's work. agimem is a hosted MCP memory server your agents read and write - persistent memory that survives the session, the project, and the tool.

See real use cases

Free to use. No credit card required. Setup takes under a minute.

Copy & paste into your agent to get started

Set up agimem as my memory server: https://agimem.dev/setup

Compatible with

ClaudeCursorWindsurfVS CodeAny MCP client

Before vs after

Your agents learn from yesterday's mistake.

Agents don't just read memory - they write to it as they work. Nobody has to remember to update an AGENTS.md or write a postmortem doc. The next agent, in any tool, just knows.

Day 1 · Cursor · learned from an incident

Last release shipped a new find-user-by-email query without the matching index. Login latency spiked for 40 minutes before the on-call rolled it back. While patching it, Cursor wrote the lesson into the Capsule on its own - no Notion postmortem, no AGENTS.md edit, no Slack thread to find later - so the next agent inherits it for free.

Without agimem

Day 8 · Claude

Add a way to look up users by phone number.

Sure - I'll add a findUserByPhone helper that runs the lookup query.

Ships without the index. Last week's incident, again.

With agimem

Day 8 · Claude

recalled from Capsule · written by Cursor after last week's incident→ ops.indexing_rule = always add an index for new where-filters on large tablesGot it - shipping the lookup with a matching idx_users_phone migration in the same PR, so we don't replay the email-index incident.

Ships safely. Lesson stays paid forward.

Cross-agent

Claude, Cursor, Windsurf, and custom agents share the same Capsule.

Cross-project

Keep a personal Capsule for your preferences and reuse it everywhere.

Cross-session

Agents update memory as they work, so the next run picks up where the last left off.

Cross-machine

Nothing to commit, nothing to sync. It's just there.

A static AGENTS.md only knows what someone remembered to write down. Capsules grow as the work happens - every fix, every clarification, every lesson, captured by the agent that learned it and ready for the next one.

How it works

Set up your MCP memory server in three steps

From zero to persistent AI agent memory in under a minute.

Step 01

01

Create a Capsule

A Capsule is an isolated key-value store. Create one per agent, project, or use case.

Step 02

02

Generate an API key

Each Capsule gets its own API key. Share it only with the agent that needs access.

Step 03

03

Connect your agent

Point any MCP-compatible client at the capsule with your key, or use the REST API. Agents can now remember things.

Show me the raw MCP config

▾

mcp-config.json

See it in action

Every memory makes the next agent smarter

Live demoDashboard

Three quick sessions across Cursor and Claude. One memory grows, gets recalled, and saves the next agent from starting from scratch.

Use cases

Built for the way agents actually work

Whether you're a solo developer or a team running fleets of agents, persistent memory means fewer repeated prompts and cleaner handoffs.

For developersFor teams

Coding conventions

Your style, every repo

Project structure, naming rules, and preferred libraries live in memory so your agent starts with your conventions instead of guessing.

e.g. “Always use Drizzle, never Prisma. Server actions live in lib/.”

Project onboarding

Drop into any codebase

Architecture notes, tech debt, and environment quirks live in memory so a new agent becomes useful quickly instead of rediscovering context.

e.g. “Monorepo with pnpm workspaces. Auth in Clerk. Deploy on Vercel.”

Personal preferences

Tone & formatting that stick

Save tone, formatting rules, and writing preferences once, then reuse them across every session without repeating the same setup prompt.

e.g. “Concise, no emojis, prefer bullets over paragraphs.”

Automation state

Resume where the job died

Job state, checkpoints, and outputs persist between runs so long-running automations resume cleanly instead of starting over.

e.g. “Last row processed: 4,281. Retry queue: empty.”

FAQ

Questions developers ask about MCP memory

Everything you need to decide fast and get your first agent connected.

What is an MCP memory server?▾

An MCP memory server lets AI agents store and retrieve persistent context through the Model Context Protocol. Instead of resetting each session, agents can remember decisions, conventions, and project state. agimem also offers a REST API for agents and tools that don't support MCP.

Which AI tools can I use with agimem?▾

agimem works with MCP-compatible clients including Claude, Cursor, Windsurf, and VS Code. For tools without MCP support, use the REST API directly.

How quickly can I set it up?▾

Most users can connect their first agent in under a minute. Create a Capsule, generate an API key, and paste one setup prompt.

Can multiple agents share memory?▾

Yes. You can point multiple agents to the same Capsule so they share context, or isolate each agent with separate Capsules for stricter boundaries.

Is agimem free to get started?▾

Yes. You can sign up and create your first Capsule without a credit card.

Ready when you are

Stop repeating yourself.

Start shipping with agents that remember.

You've seen what it does. Try it free.

• Free to use - no credit card
• Setup in under a minute
• MCP + REST API Create your first Capsule