DeepMem
Mem0-compatible persistent memory for AI agents: write facts once, recall them semantically.
Connect it
Settings → Connectors → Add custom connector
URL: https://deepmem.dev/mcpSettings → Apps & Connectors → Advanced → Developer mode
Create connector with URL: https://deepmem.dev/mcp{
"mcpServers": {
"deepmem": {
"url": "https://deepmem.dev/mcp",
"headers": {
"Authorization": "<YOUR_AUTHORIZATION>"
}
}
}
}claude mcp add --transport http deepmem https://deepmem.dev/mcp --header "Authorization: <value>"{
"servers": {
"deepmem": {
"type": "http",
"url": "https://deepmem.dev/mcp",
"headers": {
"Authorization": "<YOUR_AUTHORIZATION>"
}
}
}
}2 tools, verified live
deepmem_writeWrite conversation messages to DeepMemory for fact extraction and persistent storage. Messages are processed by an LLM to extract structured memories, which are then embedded and stored in a vector database for later semantic search. Set infer=True to enable LLM fact extraction (produces richer memories but costs one LLM call). Set infer=False to store raw messages without extraction. Returns a
deepmem_searchSearch memories stored in DeepMemory using semantic search. Returns the most relevant memories for the given query, ranked by hybrid scoring (vector similarity + BM25 keyword match + entity boost + time decay). Use this to retrieve context from past conversations before responding to the user. Memories are scoped to the user_id provided during write.
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