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
ActivityActive
ResponsivenessUnresponsive