List all named vector stores with their vector counts and dimensions. Enables overview and management of available stores for vector operations.
MIT
127,227 tools. Last updated 2026-05-05 10:49
"Overview and Information on PG Vector" matching MCP tools:
- Permanently remove incorrect or unwanted information from AI agent memory by ID, including deletion from vector index and knowledge graph.MIT
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- Diagnose embedding setup or perform manual similarity checks by creating vector embeddings for short texts. Returns the vector and dimension without indexing.MIT
- Retrieve an overview of on-chain indicator alert subscriptions including pricing, supported conditions, subscriber flow, registry addresses per chain, and subscription stats.MIT
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- Retrieve a vector stored as a binary blob in a Redis hash and convert it to a list of floats.MIT
- Retrieve detailed information about a Heroku add-on, including plan state, billing details, and configuration. Supports identifiers like add-on ID, name, or attachment name, requiring app context for attachments.
- Retrieve overview statistics from a Microsoft Word document, including paragraph count, headings, footnotes, comments, and images.MIT
- Retrieve a detailed list of all Docker Compose projects deployed on a virtual machine, including project names, statuses, and file paths. Use this tool to monitor and manage projects on your VPS instance via the Hostinger API.MIT
- Retrieve relevant AI agent memories using hybrid vector, full-text, and keyword search with optional deep search and channel filtering.MIT
- Find the K nearest neighbors to a query vector among vectors stored in Redis hash data structures.MIT
- Find similar vector embeddings in Zilliz Cloud collections using vector similarity search with optional filtering and result customization.Apache 2.0
- Create a vector index on a vector field in Baidu Vector Database to enable efficient similarity searches for AI applications.Apache 2.0
- Persist a numerical vector as a field in a Redis hash. Provide the hash key, field name (default 'vector'), and the vector to store.MIT
- Set up a Redis 8 vector similarity index using HNSW to perform approximate nearest neighbor search on hash-stored documents with float32 vectors.MIT
- Search for similar vectors in Baidu Vector Database tables while filtering results by scalar attributes to find relevant data points efficiently.Apache 2.0
- Rebuild a vector index in Baidu Vector Database to optimize search performance and maintain data integrity for AI applications.Apache 2.0
- Remove a vector index from a table in Baidu Vector Database to manage storage or modify search structures.Apache 2.0
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