A
licenseNot graded
qualityD
maintenanceEnables integrating RAG into AI agents via MCP server, supporting multiple vector database technologies.
11
MIT
vector-mcp
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TDQS
C2.6/5.0
Scored across 7 tools
Disambiguation3/5
The collection-management tools are mostly distinct, but the search tools overlap: vector_semantic_search and vector_lexical_search are clear, while vector_search is a generic search operation whose relationship to the other two is unclear. This could cause an agent to choose the generic search when a semantic or lexical search is required.
Naming Consistency4/5
All tools use a consistent vector_ snake_case prefix, and most follow a readable verb/object pattern. The main minor deviation is vector_search, which is less descriptive than the modifier_search pattern used by the other search tools.
Tool Count5/5
Seven tools is well within the appropriate range for a focused vector database server. The set covers collection lifecycle and search operations without excessive or redundant tooling.
Completeness3/5
The server covers collection creation, deletion, listing, document addition, and multiple search modes. However, document lifecycle is notably incomplete: there is no tool to update, delete, list, or get documents, and collection inspection/update operations are also missing.
Maintenance
ActivityActive
ResponsivenessSlow