"Overview and Information on PG Vector" matching MCP servers:

MCP server providing deep PostgreSQL context to AI assistants, including schema DDL, index health, foreign key associations, query execution plans, and performance statistics via read-only tools.

Enables AI assistants to query PostgreSQL databases, inspect schemas, and retrieve complete DDL with built-in read-only protection. It supports multiple database connections and allows for secure database interaction and exploration via the Model Context Protocol.

Enables MCP-compatible clients to interact with PostgreSQL databases with multi-database support and connection pooling.

In-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.

AI-native PostgreSQL health checker with 26 MCP tools for query analysis, bloat detection, migration safety, and CI integration.

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

MCP server for OpenAI Vector Store API, managing vector stores, files, file batches, and semantic search.

Enables MCP-capable agents to operate PostgreSQL and PgBouncer clusters on Kubernetes—covering discovery, pooling, tuning, backups/PITR, DR, and lifecycle—with safe-by-default read-only mode and granular opt-in security controls.

Securely connect AI assistants to PostgreSQL databases with read-only access, schema discovery, querying, and performance analysis tools.

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.

A PostgreSQL MCP server that enables querying and managing multiple databases through a single configuration file without needing separate server instances. It provides tools for executing SQL queries, listing databases, and inspecting table schemas with built-in support for read-only transactions and connection pooling.

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.

MCP server deployed on EdgeOne Pages, providing a Streamable HTTP MCP server for intelligent chat applications with tool capabilities like generating webpages.

MCP server for Apple Notes enabling read, search, write, and sync of notes with high fidelity, including styles, attachments, and bidirectional Markdown sync.

High-privilege PostgreSQL admin MCP server for database and role/grant management.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

A deployment template for running Model Context Protocol servers as Vercel Functions. It provides a foundation for developers to build and host custom tools, prompts, and resources with optimized execution for MCP client integration.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables ChatGPT to access approved local Windows folders, run commands, control the desktop, and manage session history through a permission-bounded MCP server.

Remote MCP server providing 200+ Feishu tools (messages, calendar, Bitable, etc.) for Amazon Quick Desktop, hosted on AWS Bedrock AgentCore with multi-user OAuth isolation.