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
B3.3/5.0
Scored across 2 tools
Disambiguation5/5
The two tools have clearly distinct purposes: collection management (CRUD operations on collections) and search (semantic, lexical, hybrid). There is no overlap, making it easy for an agent to select the correct tool.
Naming Consistency5/5
All tool names follow a consistent 'vector_' prefix pattern with descriptive suffixes ('collection_management', 'search'). Internal action names are uniformly snake_case, maintaining predictability.
Tool Count3/5
With only 2 tools, the server feels somewhat thin for a vector database MCP. While each tool bundles multiple actions, a few more tools (e.g., separate tools for document operations) would improve organization.
Completeness2/5
The server lacks essential operations such as updating or deleting documents, retrieving collection details, or managing metadata. These gaps would likely cause agent failures in typical workflows.
Maintenance
ActivityMaintained
ResponsivenessNo issues