<strong>AI Memory across your applications in 5 lines of code.</strong>
If you want an AI assistant working directly with Your Memory, the your memory mcp server is the bridge. AI Memory across your applications in 5 lines of code..
AI Memory across your applications in 5 lines of code.
Jean Memory provides a persistent and intelligent memory layer that enables AI applications to understand users with deep, personal context. It moves beyond simple information retrieval to sophisticated context engineering, ensuring that an AI has precisely the right information at the time of inference to provide personalized, accurate, and helpful responses.
The server is distributed via npm as @jeanmemory/react, so most clients can run it without a manual build step. Add it to your MCP client's configuration and restart the client to pick it up — the copy-paste configs for Claude Desktop, Claude Code and Cursor are on this page.
Before the server will start you need to supply 3 environment variables: YOUR_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY. Keep credentials in your client's env block or a secrets manager rather than committing them.
Knowledge and memory servers address the most frustrating trait of language models — walking into every conversation with no recollection of the last one. Your Memory sits in that group. Worth comparing against the other knowledge memory servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.
{
"mcpServers": {
"your-memory": {
"command": "npx",
"args": ["-y", "@jeanmemory/react"],
"env": {
"YOUR_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| YOUR_API_KEY | Credential the server authenticates with. | Yes |
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| GEMINI_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.