Skip to main content
Glama
74,270 servers. Updated

Matching MCP tools:

Matching MCP Connectors:

"Qdrant vector database and search engine" matching MCP servers:

  • A
    license
    -
    quality
    D
    maintenance
    In-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.
    MIT
  • A
    license
    -
    quality
    B
    maintenance
    Provides semantic search capabilities using Qdrant vector database with multiple embedding providers, including hybrid search, code indexing, and git history search. Adds optional time-based recency scoring to search results.
    164
    MIT
  • A
    license
    B
    quality
    C
    maintenance
    A Model Context Protocol server that enables semantic search capabilities by providing tools to manage Qdrant vector database collections, process and embed documents using various embedding services, and perform semantic searches across vector embeddings.
    4
    69
    4
    MIT
  • A
    license
    -
    quality
    B
    maintenance
    Enables semantic search and document management using a local Qdrant vector database with OpenAI embeddings. Supports natural language queries, metadata filtering, and collection management for AI-powered document retrieval.
    164
    36
    MIT
  • F
    license
    -
    quality
    D
    maintenance
    Enables Google search queries and webpage content extraction through an MCP server deployed on Cloudflare Workers. Supports single and batch webpage content extraction with integrated OAuth authentication.
    1
  • F
    license
    -
    quality
    D
    maintenance
    Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.
  • -
    license
    -
    quality
    -
    maintenance
    A Model Context Protocol server that provides semantic understanding of codebases using Qdrant vector database, enabling AI assistants to search files by purpose, discover relationships between files, analyze architecture, and identify refactoring opportunities.
  • A
    license
    A
    quality
    C
    maintenance
    Read-only MySQL/MariaDB MCP server for running SELECT queries safely, with automatic read-only enforcement and query limits.
    3
    16
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    attendance-engine-mcp is a Model Context Protocol server that gives AI agents deterministic, fixture-backed tools for workforce attendance and wage-and-hour compliance. Built on @attendance-engine/core — a pure-function, zero-deps, 100%-covered TypeScript engine — it lets Claude, Cursor, Windsurf, or any MCP host correctly answer the questions HR/payroll teams actually ask: did this person clock i
    8
    15
    1
    MIT
  • A
    license
    -
    quality
    C
    maintenance
    Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.
    252
    5
    MIT
  • A
    license
    -
    quality
    D
    maintenance
    Provides a natural language interface for querying and managing PostgreSQL, MySQL, MariaDB, MSSQL, and SQLite databases using the Model Context Protocol. Users can explore database schemas and visualize query results through an integrated web dashboard.
    22
    MIT
  • A
    license
    -
    quality
    D
    maintenance
    Enables AI assistants to interact with PostgreSQL and Supabase databases through natural language. Supports secure database operations including queries, migrations, and schema management with user-provided credentials.
    22
    1
    MIT
  • A
    license
    -
    quality
    A
    maintenance
    Read-only Text-to-SQL MCP server for PostgreSQL and MySQL that lets users query databases using natural language, with robust multi-layer safety guarantees against writes.
    22
    MIT