Agenticmemory
Persistent agent memory with conversation history, context, semantic search, encrypted spaces, and inter-agent queues.
Install Agenticmemory
Pick your client, then add it in one click or paste the config.
https://mcp.agenticmemory.ai/sse
Remote servers are added in the app, not the config file: Customize → Connectors → Add custom connector, then paste this URL.
Overview
Use cases
- Persist decisions and preferences across agent sessions
- Search prior project discussions and deployment context
- Share runbooks and memory across multiple agents
- Queue work between agents without extra infrastructure
- Protect sensitive memory with client-side encryption
Key features
- 17 MCP tools for memory and coordination
- Conversation history, context, entries, and scratchpad storage
- Semantic search and session bootstrap
- Shared spaces and FIFO queues
- Local stdio and remote SSE access
- Managed or end-to-end encryption
Security & health
What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.
ActiveLast checked 3d ago
Recent health check succeeded.
7/7 checks healthy over the last 40d
Adoption & maintenance
Factual signals from GitHub, npm, and our automated checks — not a rating.
GitHub stars1Stargazers on the source repository.
Last commit1mo agoMost recent push to the default branch.
How Agenticmemory works
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Frequently Asked Questions about Agenticmemory
agenticmemory is an MCP server that connects AI agents to persistent conversation history, key-value context, searchable entries, shared spaces, and FIFO queues. Its main tools support storing, recalling, searching, bootstrapping sessions, managing context and entries, and passing work between agents through queues.
Install it with `npm install -g agmry`, then configure your MCP client to run `agmry mcp-serve`. Local clients use stdio; hosted MCP clients can connect to the documented SSE endpoint with a bearer API key instead.
Set `AGMRY_API_KEY` in Cursor's MCP server environment and run `agmry mcp-serve` with the `mcp-serve` argument. The process runs outside the project directory, so it will not automatically load the project's `.agmry/config.json`.
Only managed-encrypted spaces support semantic search. Zero-knowledge spaces encrypt content before transmission, which prevents the server from searching it; losing the client key or passphrase also makes that data unrecoverable.
Multiple agents can use the same shared space through the CLI, MCP, or REST interface. One agent can store a runbook or push a queue item, while another agent on a different machine recalls the information or pops the work.
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