The @littlebigbrain/mcp server provides 11 tools for searching, querying, writing, and managing a knowledge graph from AI clients like Claude, Cursor, or Codex.

Read / Retrieval

• lbb_search — Hybrid (BM25 + vector) natural-language retrieval with multi-query fusion and optional graph path following from seed entities.

• lbb_ask — Ask a natural-language question and get a grounded, cited answer synthesized from the graph, or retrieve grounding evidence only.

• lbb_decode — Given two entity names, identify the relation between them using type-signature narrowing and a fine-tuned model.

• lbb_ground — Resolve free text to real vocabulary items (types, relations, properties) via autocomplete, embedding/lexical snap, or a full groundability audit.

• lbb_inspect — Browse ontology, schema, SHACL conformance, inference rules, entity metadata, edges, state, history, provenance, and perform graph traversals.

• lbb_query — Run SPARQL queries, structured analytics (filters, aggregations, grouping), SHACL validation, inference, and retrieval-premise analysis.

Write / Mutation

• lbb_commit — Write triplets (edges), typed scalar properties, and embeddings; retract facts; or label search results for relevance feedback.

• lbb_observe — Store conversation episodes and commit extracted facts onto an isolated branch, with optional auto-merge after SHACL validation.

• lbb_configure — Define or evolve ontologies (add/rename/remove entity types, relations, properties), publish SHACL shape bundles, and manage inference rules.

• lbb_branch — Create isolation branches (fork) and perform validated merges (replay + SHACL check) back onto the parent branch.

• lbb_index — Rebuild or refresh BM25, vector, and adjacency indexes so newly committed facts become searchable.

All tools support paging, snapshot pinning (as-of / commit sequence), detail levels, and idempotent writes. The server can be deployed via a hosted OAuth endpoint, as a local stdio process, or embedded as an HTTP server within a TypeScript application.

1. Click on "Install Server".

2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.

3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@@littlebigbrain/mcp search for entities related to 'Project Apollo'"

That's it! The server will respond to your query, and you can continue using it as needed.

Here is a step-by-step guide with screenshots.