Understanding Document Embeddings, Knowledge Graphs, and Vector Representations

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Understanding Document Embeddings, Knowledge Graphs, and Vector Representations

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Why this server?
This server allows interaction with Neo4j graph databases, which aligns directly with the 'graph' and 'knowledge' terms in the query.
Neo4j MCP Server
ujjalcal
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security
F
license
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quality
An MCP server that enables graph database interactions with Neo4j, allowing users to access and manipulate graph data through natural language commands.
Last updated -
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.
Logseq MCP Server
dailydaniel
A
security
A
license
A
quality
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.
MCP DuckDB Knowledge Graph Memory Server
IzumiSy
A
security
A
license
A
quality
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
95
38
TypeScript
MIT License
Why this server?
This server allows retrieving content from different knowledge bases using semantic search, matching the 'knowledge' part of the request.
Knowledge Base MCP Server
jeanibarz
A
security
A
license
A
quality
Provides tools for listing and retrieving content from different knowledge bases using semantic search capabilities.
Last updated -
2
10
TypeScript
The Unlicense
Why this server?
Facilitates knowledge graph representation and uses vector embeddings for semantic similarity, aligning with 'graph', 'knowledge', and 'vector' terms.
MCP Memory Server with Qdrant Persistence
delorenj
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security
F
license
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quality
Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.
Last updated -
33
4
TypeScript
Why this server?
This server is relevant due to its 'vector' related capabilities along with general document processing features.
Vectorizeofficial
vectorize-io
A
security
A
license
A
quality
Vectorize MCP server for advanced retrieval, Private Deep Research, Anything-to-Markdown file extraction and text chunking.
Last updated -
3
60
67
JavaScript
MIT License
Why this server?
The description mentions integration with Weaviate, which is a vector search engine.
MCP Server Weaviateofficial
weaviate
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security
F
license
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quality
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.
Last updated -
126
Go
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
Jina AI MCP Server
Sheshiyer
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security
A
license
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quality
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.
MCP Chat Analysis Server
rebots-online
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security
A
license
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quality
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
MCP Documentation Service
alekspetrov
A
security
A
license
A
quality
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.
Last updated -
14
346
11
TypeScript
MIT License

Understanding Document Embeddings, Knowledge Graphs, and Vector Representations

Vectorizeofficial

MCP Server Weaviateofficial