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Understanding Document Embeddings, Knowledge Graphs, and Vector Representations

  • Why this server?

    This server allows interaction with Neo4j graph databases, which aligns directly with the 'graph' and 'knowledge' terms in the query.

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    An MCP server that enables graph database interactions with Neo4j, allowing users to access and manipulate graph data through natural language commands.
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    Python
  • Why this server?

    This server allows LLMs to programmatically interact with Logseq knowledge graphs, aligning with the 'graph' and 'knowledge' terms in the query.

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    A server that enables LLMs to programmatically interact with Logseq knowledge graphs, allowing creation and management of pages and blocks.
    Last updated -
    10
    17
    Python
    MIT License
  • Why this server?

    This server is relevant because it provides a knowledge graph implementation using DuckDB, aligning with the 'graph' and 'knowledge' terms.

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    A memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.
    Last updated -
    8
    36
    31
    TypeScript
    MIT License
    • Apple
  • Why this server?

    This server allows retrieving content from different knowledge bases using semantic search, matching the 'knowledge' part of the request.

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    Provides tools for listing and retrieving content from different knowledge bases using semantic search capabilities.
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    10
    TypeScript
    The Unlicense
    • Linux
    • Apple
  • Why this server?

    Facilitates knowledge graph representation and uses vector embeddings for semantic similarity, aligning with 'graph', 'knowledge', and 'vector' terms.

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    Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.
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    TypeScript
    • Linux
    • Apple
  • Why this server?

    This server is relevant due to its 'vector' related capabilities along with general document processing features.

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    Vectorize MCP server for advanced retrieval, Private Deep Research, Anything-to-Markdown file extraction and text chunking.
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    17
    JavaScript
    MIT License
    • Apple
    • Linux
  • Why this server?

    The description mentions integration with Weaviate, which is a vector search engine.

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    The MCP Server for Weaviate facilitates integration with Weaviate using a customizable Python-based server, enabling interaction with Weaviate databases and OpenAI APIs via configurable URL and API keys.
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    44
    Python
    GPL 3.0
    • Apple
  • Why this server?

    Enables semantic search, image search, and cross-modal search functionalities through integration with Jina AI's neural search capabilities, relates to vector

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    Enables semantic search, image search, and cross-modal search functionalities through integration with Jina AI's neural search capabilities.
    Last updated -
    1
    JavaScript
    MIT License
  • Why this server?

    Facilitates semantic analysis of chat conversations through vector embeddings and knowledge graphs, covering 'vector' and 'knowledge' aspects.

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    Facilitates semantic analysis of chat conversations through vector embeddings and knowledge graphs, offering tools for semantic search, concept extraction, and conversation pattern analysis.
    Last updated -
    8
    Python
    MIT License
  • Why this server?

    This server's description mentions managing markdown documents and metadata handling capabilities aligns with search terms doc and knowledge

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    A Model Context Protocol implementation that enables AI assistants to interact with markdown documentation files, providing capabilities for document management, metadata handling, search, and documentation health analysis.
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    346
    11
    TypeScript
    MIT License
    • Apple
    • Linux