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198,096 tools. Last updated 2026-06-13 04:05

"General Information or Concepts Related to Memory" matching MCP tools:

  • Find medical concepts similar to a reference concept, name, or query using semantic, lexical, or hybrid algorithms. Explore related concepts and build phenotype sets.
    MIT
  • Discover semantically related concepts using ConceptNet's similarity algorithms to expand exploration, find related terms, and understand semantic neighborhoods.
    GPL 3.0
  • Look up a concept to find all variants, related concepts, naming conventions, function signatures, and file locations. Resolves questions like 'what is X', 'what does X mean', or 'where is X used'.
    MIT
  • BFS walk from a memory node to map related concepts, supersession chains, or decision clusters. Returns neighbor nodes with typed edges. Read-only; use after searching memories to explore connections.
    MIT
  • Add multiple memory nodes with automatic similarity linking. Computes embeddings and creates connections between related concepts, files, or notes for semantic intelligence.
    MIT
  • Find how two concepts are connected by retrieving relationships between them using their labels, returning only live entries.
    MIT

Matching MCP Servers

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    Provides LLMs with full PostgreSQL database access, including tools for query execution, schema management, and data export. It also features a dedicated insights system for storing business memos and supports both local stdio and remote HTTP transport.
    Last updated
    MIT

Matching MCP Connectors

  • Cultural color and colour intelligence API. Every colour anchored to a named person, a documented year, and a consequence. 34 archives spanning literary, cultural, pigment, and national traditions. Ask it what color could get you executed in the Ottoman Empire.

  • Cloudflare Workers MCP server: agent-memory

  • Store important facts, preferences, decisions, and concepts as atomic nodes in a persistent knowledge graph. Use after learning key information from a user to build structured memory.
    Apache 2.0
  • Traverse knowledge graphs from seed nodes to discover related concepts and relationships for depth-first exploration and structured insight generation.
    Sleepycat
  • Traverse the knowledge graph from a starting memory to discover related concepts. Specify depth and relationship types to find connections.
    AGPL 3.0
  • Search Tenzir documentation by keyword to find operators, functions, or concepts, and explore related content through cross-references for comprehensive understanding.
    Apache 2.0
  • Search Redis documentation and knowledge base to find information on concepts, data structures, features, and use cases including caching, session management, and semantic search.
    MIT