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607,444 tools. Updated 2026-09-24 16:54

"Resources for Exploring Deep Thinking Concepts" matching MCP tools:

  • Retrieve comprehensive brain statistics across multiple views: overview, domain breakdown, thinking pulse, conversations, embeddings, GitHub repositories, and markdown documents. Gain insights from aggregated cognitive data.
    MIT
  • Traverse up the concept hierarchy by retrieving broader (parent) concepts from a starting URI up to a specified depth. Ideal for exploring parent concepts in SKOS vocabularies.
    MIT
  • Reconstruct your cognitive state for any domain: retrieve where you left off, including thinking stage, open questions, decisions, concepts, and emotional tone to resume your train of thought.
    MIT

Matching MCP Servers

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    Advanced cognitive thinking MCP server with DAG-based thought graph, multiple reasoning strategies, metacognition, and self-evaluation. A significant evolution beyond sequential-thinking MCP, providing structured deep reasoning with graph-based thought management.
    6
    23 npm
    13
    MIT

Matching MCP Connectors

  • Find relevant Smart‑Thinking memories fast. Fetch full entries by ID to get complete context. Spee…

  • Autonomous deep research reports merging PSFK trend graphs with citable sources.

  • Search the knowledge graph for entities and their relationships. Discover connections between people, projects, and concepts.
    MIT
  • Find medical concepts using plain language. Understands clinical meaning, e.g., 'heart attack' maps to 'Myocardial infarction'.
    MIT
  • Find images across the web to illustrate concepts, locate specific pictures, or discover visual resources. Returns images as base64-encoded JPEGs or URLs with metadata.
    Apache 2.0
  • Search OHDSI standardized vocabularies to find OMOP concept IDs for medical terms, returning matching concepts with IDs, names, vocabulary, domain, and standard status.
    MIT
  • List recurring concepts across memories with filters for entity type, minimum mentions, and limit.
    MIT
  • Compare two concepts by retrieving source-backed evidence from your local knowledge base. Specify focus areas to identify similarities, differences, and relationships across documents.
    MIT
  • Rebuild the vector index for a knowledge bundle with incremental updates by default or a full rebuild. Yields a JSON summary of added, updated, removed, and total concepts.
    Apache 2.0
  • Analyze an image from a local path or URL and answer questions about it. Provide a source and a question; optional deep thinking mode yields more detailed responses.
    MIT