"Information about PG Vector" matching MCP servers:

Archived MCP server for PostgreSQL health monitoring; functionality merged into pg-dash.

Enables users to retrieve and structure shipment tracking information from DB Schenker's website using natural language queries.

Gives Claude Code read-only access to a student's eNauczanie PG (Moodle) account, enabling retrieval of courses, deadlines, grades, announcements, forum discussions, and quiz reviews using the student's web service token.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

Enables asking natural language questions about local videos, using Whisper transcription, ChromaDB vector storage, and Groq for timestamped answers via MCP.

Connects MCP-compatible coding agents to VMware vCenter to query information about virtual machines, hosts, clusters, datastores, datacenters, and networks.

A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Enables a single MCP server for interacting with multiple vector databases through pluggable backends, starting with Pinecone. It supports schema-aware index management, upserts, hybrid search, embeddings, TTL conventions, and namespace operations.

A shared, persistent MCP memory server for coding agents that enables storing and retrieving project decisions and context across different tools like Claude Code, Codex, and Cursor using semantic vector search.

Enables building and querying vector-based knowledge graphs with node and edge management and semantic search.

Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.

A production-grade MCP server for integrating RAG into AI agents, supporting multiple vector databases with enterprise security and dynamic tool selection.

Enables searching and retrieving information about anime, manga, and related content via the Bangumi API.

Enables agents to track causal relationships, reconcile concurrent state changes, and coordinate consensus across distributed networks using vector clocks, CRDTs, gossip, and quorum-based protocols.

Enables LLMs to interact with Rememberizer Vector Store for semantic search, document creation, deletion, and modification.

A Model Context Protocol server that provides natural language access to Cortex API, enabling users to query information about their system's structure and make faster decisions about services, incidents, and team responsibilities.

A Kubernetes management MCP server that provides interfaces for getting information about Kubernetes clusters, performing operations, monitoring status, and analyzing resources.

Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.

Provides access to government development, geography and land information data through a FastMCP interface, including data on new building plans processed by the Building Authority.

Enables storing and retrieving information using semantic search with Qdrant vector database. Acts as a memory layer for LLMs to persistently store and semantically search through information and metadata.

Turns your Readwise library into a blazing-fast semantic search engine with a streaming MCP server for LLM clients, supporting vector search, nightly syncs, and deployment on serverless platforms like Vercel.

A secure vector-based memory server that provides persistent semantic memory for AI assistants using sqlite-vec and sentence-transformers. It enables semantic search and organization of coding experiences, solutions, and knowledge with features like auto-cleanup and deduplication.

An MCP server that provides detailed information about your development environment to the Cursor code editor, enabling more context-aware assistance.

Enables hybrid retrieval over interpretable Gemini documentation knowledge graphs through eight MCP tools, combining vector, keyword, and graph-boosted search with deprecation filtering.

Deterministic evidence about embedding spaces and vector indexes for agents: hubness, anisotropy, collapse, distance concentration, ANN recall, HNSW/IVF sweeps. CLI + MCP server.

Enables users to query information about LPDP scholarship financial disbursement using RAG with Pinecone vector search and Gemini 2.0 Flash, answering questions about funding components, deadlines, living allowances, and required documents.

Enables semantic search and management of Zotero reference libraries using PostgreSQL with pg-vector and OpenAI/Ollama embeddings. Provides AI-powered search, full-text extraction, metadata access, annotations, notes, tags, and collections management.