Memento MCP: Knowledge graph memory system for LLMs
Memento MCP: Knowledge graph memory system for LLMs
Scalable, high performance knowledge graph memory system with semantic retrieval, contextual recall, and temporal awareness. Provides any LLM client that supports the model context protocol (e.g., Claude Desktop, Cursor, Github Copilot) with resilient, adaptive, and persistent long-term ontological memory.
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Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| diagnose_vector_search | Information about the Neo4j vector index, embedding counts, and search functionality |
| force_generate_embedding | Forces the generation of an embedding for a specific entity |
| debug_embedding_config | Information about the current embedding service configuration |
| Variable | Description | Required |
|---|---|---|
| MEMORY_STORAGE_TYPE | Configuration value read at startup. | Optional |
| NEO4J_URI | Configuration value read at startup. | Optional |
| NEO4J_USERNAME | Configuration value read at startup. | Optional |
| NEO4J_PASSWORD | Configuration value read at startup. | Optional |
| NEO4J_DATABASE | Configuration value read at startup. | Optional |
| NEO4J_VECTOR_INDEX | Configuration value read at startup. | Optional |
| NEO4J_VECTOR_DIMENSIONS | Configuration value read at startup. | Optional |
| NEO4J_SIMILARITY_FUNCTION | Configuration value read at startup. | Optional |
Store entities, relations and observations in a local knowledge graph with the reference Memory MCP server.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.
Chat with your second brain — search, read and write vault notes through the Local REST API.
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