vector-knowledge-graph-mcp
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Related Servers
- AlicenseAqualityDmaintenanceEnables AI assistants to search, browse, and save to a semantic knowledge graph with vector search and hierarchical organization.51MIT
- FlicenseCqualityDmaintenanceCombines a knowledge graph with RAG (Retrieval-Augmented Generation) capabilities for semantic code indexing and search. Enables creating entity relationships, managing observations, and performing semantic searches across indexed codebases.13-
- AlicenseNot gradedqualityDmaintenanceFacilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.6 npm24MIT
- AlicenseBqualityBmaintenanceProvides LLM clients with a persistent, scalable knowledge graph memory system that supports semantic retrieval, contextual recall, and temporal awareness.21311 npm1MIT
- FlicenseNot gradedqualityDmaintenanceCombines Neo4j graph database with vector search using OpenAI embeddings for intelligent semantic search across knowledge graphs.3-
- FlicenseNot gradedqualityDmaintenanceEnables creation and management of knowledge graphs with entities, relationships, and observations through HTTP streaming. Supports persistent storage, search functionality, and CRUD operations for building and querying interconnected knowledge bases.2-
TDQS
Scored across 5 tools
Each tool has a distinct purpose: adding nodes, adding edges, semantic search, gap analysis, and compliance tracing. No two tools overlap in functionality.
All tool names use snake_case, but the verb pattern is not entirely uniform: add_node and add_edge follow verb_noun, while semantic_node_search and trace_compliance_chain are less consistent. Still, the naming is clear and predictable overall.
Five tools is an appropriate scope for a knowledge graph server, covering creation, search, analysis, and domain-specific traversal without being overwhelming or too sparse.
The set covers core operations (add, search, analyze) and domain-specific needs (compliance tracing), but missing update and delete operations for nodes and edges, which are common in knowledge graph management.