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Search, manage, verify, and reindex documents in a local vector knowledge base.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Lore DB MCP Server" yet — see the docs or source repo.
Use the Lore DB MCP Server to run a semantic search in the local knowledge base for the 5 documents most relevant to "vector database performance optimization", and return the title, summary, and similarity score.
A ranked list of relevant documents with titles, summaries, and match scores.
Using the Lore DB MCP Server, create a new document titled "MCP Integration Guidelines" with content describing the differences and use cases of HTTP and stdio access, then verify that the document was saved successfully and is searchable.
A creation result with document ID plus confirmation that the entry was stored and can be searched.
Use the Lore DB MCP Server to reindex the local knowledge base and report the number of processed documents, total time taken, and whether any records failed.
An execution report for the reindexing job, including counts, duration, and any errors.
Search and retrieve local documents semantically for faster AI-powered knowledge access.
Provide AI agents shared team context, session captures, and structured documentation.
Let AI assistants query and edit worldbuilding data with review-gated changes.
Index a knowledge base into Chroma and retrieve relevant document fragments.
Index and search local Markdown and PDF knowledge bases efficiently.
Manage local semantic dataspaces, ingest documents, and run semantic search via MCP.