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Store and retrieve semantic memories for AI apps with similarity search.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-lance-db" yet — see the docs or source repo.
Use mcp-lance-db to save the following user preferences as semantic memory: the user is Li Ming, prefers summaries of English technical articles, and likes concise answers. Add searchable tags to this memory.
A confirmation that the memory was stored, including identifiers or metadata for later retrieval.
Use mcp-lance-db to retrieve memories most similar to 'the user wants brief answers and prefers technical content summaries,' and return the top 5 matches with similarity scores.
A ranked list of matching memories with content, similarity scores, and relevant metadata.
Use mcp-lance-db to batch store the following project knowledge as semantic memories: product name, target users, core features, and FAQs; then test retrieval for 'automation features for small and midsize teams' and show the matches.
First, a batch write result; then a semantic retrieval example showing the knowledge base can be recalled correctly.
Give AI agents persistent memory with semantic recall and maintenance tools.
Lightweight vector memory for AI agents to store, search, and delete memories.
Give AI assistants persistent memory with tagged retrieval, links, and source references.
Give AI agents vector memory to reuse past solutions for similar requests.
Provide persistent local semantic memory for MCP tools to store and search notes.
Turn local notes into a private searchable knowledge base for AI assistants.