Mnemo MCP-native memory database for AI agents. Mnemo (from Greek mneme — memory) is an embedded database whose primitives are REMEMBER, RECALL, FORGET, an…
Mnemo MCP-native memory database for AI agents. Mnemo (from Greek mneme — memory) is an embedded database whose primitives are REMEMBER, RECALL, FORGET, and SHARE — exposed as MCP tools that any AI agent can connect to directly. Quickstart 1. Build cargo build --release 2. Configure your AI agent Add to your MCP client configuration (e.g. Claude Desktop, Cursor, etc.): JSON{ "mcpServers": { "mnemo": { "command": "./target/release/mnemo", "args": ["--db-path", "./agent.mnemo.db"], "env": { "OPENAI_API_KEY": "sk-..." } } } } 3. Use it Your AI agent now has persistent memory with 10 MCP tools: ToolDescriptionmnemo.rememberStore a new memory with semantic embeddingsmnemo.recallSearch memories by semantic similarity, keywords, or hybridmnemo.forgetDelete memories (soft delete, hard delete, decay, consolidate, archive)mnemo.shareShare a memory with another agentmnemo.checkpointSnapshot the current agent memory statemnemo.branchCreate a branch from a checkpoint for experimentationmnemo.mergeMerge a branch back into the main statemnemo.replayReplay events from a checkpointmnemo.delegateDelegate scoped, time-bounded permissions to another agentmnemo.verifyVerify SHA-256 hash chain integrity Access Protocols ProtocolCrateUse CaseMCP (stdio)mnemo-mcp
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