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605,282 tools. Updated 2026-09-23 23:53

"How to Query a Knowledge Graph Using an Ontology" matching MCP tools:

Matching MCP Servers

  • A
    license
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    quality
    C
    maintenance
    A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.
    MIT
  • A
    license
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    quality
    A
    maintenance
    Enables fast, targeted queries against an Obsidian vault knowledge graph using tools like search, neighbor traversal, and pathfinding, without needing to load the full graph into LLM context.
    2
    MIT

Matching MCP Connectors

  • Explore a memory knowledge graph to find connected memories, hub nodes, or paths between memories. Query neighbors, hubs, or paths filtered by domain and relationship.
    -
  • Answer factual questions from a shared knowledge graph, grounded in evidence with citations. Abstains when the graph lacks knowledge.
    MIT
  • List entities in the knowledge graph, optionally filtered by type, to obtain an overview or entity names for graph queries. Supports D3-compatible JSON output.
    MIT
  • Generate an openCypher query from natural language descriptions for TigerGraph graphs. Specify graph name to get Cypher syntax wrapped in INTERPRET OPENCYPHER QUERY format.
    Apache 2.0
  • Search persistent memory using semantic similarity to retrieve relevant memories and related knowledge graph facts.
    MIT
  • Query the knowledge graph to find entities connected to a given entity, revealing relationships and dependencies within specified depth.
    MIT
  • Search the CodeLogic knowledge graph to retrieve code and data architecture dependencies. Use a text query or identity prefix, with optional scan space and view filters.
    Mozilla Public 2.0
  • Query project knowledge-graph context with tier filtering. Specify budget and pattern to get relevant evidence-anchored facts.
    MIT
  • Explore how concepts in your notes connect by querying a knowledge graph of memories and wiki pages. Retrieve an entity's relations with source citations, or list top hub entities for orientation.
    MIT
  • Explore the knowledge graph hierarchy from a starting node, viewing three levels of children to understand knowledge organization before searching or saving.
    MIT
  • Persist entities and relations into a typed knowledge graph with ontology validation, provenance, and contradiction detection. Add source text and summary to support lexical recall.
    Apache 2.0
  • Rank knowledge-graph nodes by importance using PageRank, optionally personalized by query, to surface top concepts for condensation, search ranking, and documentation sourcing.
    Apache 2.0