@littlebigbrain/mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LBB_GRAPH | No | Target graph (default: main) | |
| LBB_BRANCH | No | Target branch (default: main) | |
| LBB_API_KEY | Yes | API key for authentication | |
| LBB_BASE_URL | Yes | Base URL of the Little Big Brain server, e.g., https://db.eu.littlebigbrain.com | |
| LBB_MCP_HOST | No | Host to bind for HTTP server (default: 127.0.0.1) | |
| LBB_MCP_PATH | No | Path for MCP endpoint (default: /mcp) | |
| LBB_MCP_ALLOWED_HOSTS | No | Comma-separated allowed Host headers for DNS-rebinding protection | |
| LBB_MCP_ALLOWED_ORIGINS | No | Comma-separated allowed Origin headers for CORS |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| lbb_rdfA | Store and extend complete RDF/OWL documents through MCP. import accepts Turtle/N-Triples/N-Quads/TriG without conversion; update executes INSERT DATA for additive edits. Replacing/removing axioms is unsupported; use a new versioned LBB graph for a revised document. Named RDF graphs are unsupported; Turtle/N-Triples use the default graph, and dataset formats must contain only default-graph quads. These write graph facts, distinct from lbb_configure's native schema metadata. A first RDF write selects RDF-native storage, which refuses later property-graph commits; choose the write workflow before bootstrap. Retries deduplicate by content unless idempotency_key is supplied. A completed write schedules publication; inspect action=publication and verify using lbb_query entailment=owl. |
| lbb_inspectA | Read graph context and exact graph facts. Actions: guide, graphs, publication, ontology, ontology_conformance, schema, ontology_search, metadata, entity, state, history, transitions, why. graphs works before bootstrap; publication reports whether writes are queryable. ontology and schema return complete entries with page_size, section and cursor; follow next until absent. schema reads active native ontology/SHACL metadata without running validation. Query asserted RDF/OWL axioms separately with lbb_query. ontology_conformance serves the durable report referenced by the pinned published root. entity returns one node's metadata, scalar attributes, bounded Base-backed edge neighborhood, history, and observations. Use lbb_query with SPARQL property paths for precise path selection. |
| lbb_queryA | Analytical and expert reads. Modes: structured (SPARQL-subset JSON body), sparql (SPARQL text), analyze. SPARQL is the only query surface. Relations are https://littlebigbrain.com/r/NAME and types https://littlebigbrain.com/class/NAME (both lowercased); entities are content-addressed, so anchor a named one by its rdfs:label rather than building its IRI. Structured and text queries pin one published watermark for the request. |
| lbb_modelsB | Read model-training inputs or compare retrieval configurations over one pinned published snapshot. shadow_eval takes the API ShadowEvalRequest body; dataset actions return bounded training examples at an optional signal split. |
| lbb_commitA | Write graph facts, retract them, or label ranked results. mode=facts writes triplets/embeddings/properties; mode=retract removes a wrongly-added fact (by edge or by entity) without a full reset; mode=search_feedback stores query/result relevance labels (Feedback grades: 3=ideal/good, 1=partial, 0=bad; include query, search_id when available, target, rank, score). Explicit idempotency_key wins; when omitted, MCP derives a stable content hash so content-identical retries dedupe. Facts mode defaults edge_idempotency to append; pass skip_unchanged for re-runnable backfills. |
| lbb_configureA | Manage native schema metadata. Actions: define_ontology (friendly spec with super_types), evolve_ontology (ordered edits including add_super_types), publish_schema (SHACL activation). All support dry_run previews. Definition/import here extracts native metadata; it does NOT store the complete RDF/OWL document as queryable graph facts. Use lbb_rdf import for full OWL and lbb_rdf update for additive INSERT DATA revisions; RDF deletions are unsupported. Publish_schema accepts unchanged ontology plus shapes; use define/evolve for native ontology changes. Publication enqueues durable conformance; a preview does not validate the whole graph. |
| lbb_branchA | Branch lifecycle. Actions: create (fork a new branch off from_branch — the tool's |
| lbb_observeA | Remember a conversation: store the turns verbatim as an EPISODE evidence entity, then anchor + gate the supplied facts on an observe branch (LLM extraction cannot poison the main graph). Facts with both endpoints already in the graph are anchored; unanchored facts need confidence >= 0.8 to mint new entities, else they come back needs_review. auto_merge merges the branch onto the scoped branch when SHACL validation is clean (the validate-then-merge). Server flag-gated (--enable-observe). This build takes caller-extracted facts (each with a structured triplet); bare statements come back needs_review. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: lbb_rdf handles RDF/OWL document import/update, lbb_commit writes/retracts graph facts and feedback, lbb_inspect reads graph context/metadata, lbb_query executes SPARQL, lbb_configure manages schema metadata, lbb_branch handles branch lifecycle, lbb_models provides model training data, and lbb_observe captures conversations. Despite some overlap in write operations, the descriptions explicitly delineate boundaries (e.g., lbb_rdf vs. lbb_commit), eliminating ambiguity.
All tools share the 'lbb_' prefix and use lowercase single-word names, which is readable and predictable. However, the second part mixes verbs (inspect, query, commit, configure, observe) and nouns (rdf, branch, models), so it does not follow a strict verb_noun pattern. The consistency of the prefix and clarity of each name mitigate this minor inconsistency.
With 8 tools, the server is well-scoped for its domain (a knowledge graph with RDF support, schema management, branching, and observation). This falls comfortably within the ideal 3-15 range, and each tool provides a distinct capability without redundancy.
The server covers core lifecycle operations: RDF import/update, graph fact writes/retraction, SPARQL querying, schema definition/evolution, branching/merging, model data access, and observation. However, there is no direct RDF deletion (only additive updates via lbb_rdf and retraction via lbb_commit), and no tool for exporting or bulk deleting graph data, leaving minor gaps that agents can work around.