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Unified gateway for semantic search, graph queries, and knowledge routing.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "kb-gateway" yet — see the docs or source repo.
Use kb-gateway to run a semantic search over the learning corpus for content about how vector databases and knowledge graphs work together, and return summaries of the 5 most relevant results.
Returns 5 highly relevant corpus summaries to quickly locate useful knowledge.
Use kb-gateway to query the knowledge graph and find the relationships between retrieval-augmented generation, Pinecone, and Neo4j, then present the nodes and connections in a structured list.
Outputs related entities and their relationships for clearer understanding of concept connections.
Use kb-gateway to decide whether this question should use semantic search or a graph query: 'What are the prerequisite topics and dependency relationships for a course subject?' Then run the best query and return the result.
First provides the routing decision, then returns the matching knowledge result with a brief explanation.
Query a learning corpus and knowledge graph through a unified MCP gateway.
Connect AI agents to Korean commerce, payments, messaging, and government APIs.
Connect multiple MCP servers through one gateway for unified tool access.
Aggregate MCP servers and find tools through natural language semantic search.
Give AI agents local-first structured memory with search and timeline tracking.
Centralize knowledge, run semantic search, ingest documents, and generate RAG answers.