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

Automates SEO report generation from Google Drive data via Claude Desktop, supporting multiple data types and exporting reports in DOCX, HTML, PPTX, and PNG formats.

Integrates RAG into AI agents via MCP Server, supporting multiple vector database technologies for collection management and search operations.

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

Enables integrating RAG into AI agents via MCP server, supporting multiple vector database technologies.

A lightweight Postgres MCP server for safe database exploration and query analysis, read-only by default, with multi-database support.

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.

Provides an MCP server that tracks open loops (pending decisions or replies) across email, agent sessions, and other channels, enabling agents to query what is waiting on whom.

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

Enables semantic search across PostgreSQL, TimescaleDB, and PostGIS documentation to help AI coding assistants write better PostgreSQL code.

Enables MCP clients to inspect and query PostgreSQL databases through per-endpoint bearer-token authentication, SQL guarding, and comprehensive audit logging, while a web UI manages connections, endpoints, roles, and audit records.

Enables AI assistants to safely explore PostgreSQL schemas, inspect sample rows, draft queries, and read EXPLAIN plans through a read-only enforced interface for MCP clients.

Enables semantic and full-text search over markdown notes, with tools to create, edit, move, and delete notes, all through MCP. Runs entirely locally using Ollama for embeddings and SQLite for storage, working with Obsidian or standalone.

Enables local vector database operations with a Pinecone-compatible API, supporting exact and approximate search, metadata filtering, and semantic text queries over MCP.

A Model Context Protocol server for PostgreSQL that enables database operations like querying, schema inspection, performance analysis, and administration through a JSON-RPC 2.0 interface.

Enables agents to turn documents into vectors, perform approximate nearest neighbor search with HNSW, and filter by metadata via MCP tools for RAG workflows.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

Enables fetching Google's AI Overview answers and cited sources as structured JSON, with support for batch queries and country/language targeting.

PostgreSQL MCP server that converts natural language to SQL and executes queries, with multi-database support and robust read-only safety checks.

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

A secure PostgreSQL Model Context Protocol server that provides read-only database access through tools like schema listing, object inspection, query execution, and EXPLAIN analysis, with database-enforced access control via read-only transactions and a minimal role rather than SQL text parsing.

Diagnoses and manages PostgreSQL logical replication including slot WAL retention, walsender lag, stuck subscriptions, and provides gated remediation tools for safe AI-driven operations.

Enables read-only PostgreSQL interaction through safe query execution, query planning, table and column inspection, and privilege checks, with multi-layer defenses against write operations and transaction-control exploits.

Provides SQL-backed semantic search over indexed notes using pgvector, exposing tools to search and list note sources via natural language.

Enables LLM assistants to analyze PostgreSQL query execution plans with EXPLAIN and receive structured reports highlighting performance bottlenecks, all through read-only database access.

Enables read-only exploration of a Postgres database using natural language, with multiple safety layers to prevent any modifications.

Enables AI agents to run read-only Postgres bloat diagnostics, returning per-table and per-index verdicts with supporting evidence, actionable fixes, and timeline history. It also identifies blocking sessions and can take a one-shot throwaway snapshot for live production diagnosis without touching stored timeline data.

Gives agents read-only access to PostgreSQL databases, enabling them to inspect schemas, sample rows, compare stands, view query plans, and run read-only SQL through a single entry point.

Enables users to interact with PostgreSQL databases using natural language, converting questions into validated, safe SQL queries and returning execution results with confidence scoring.

Enables read-only PostgreSQL schema exploration through natural language, including tables, indexes, sizes, sample rows, and query plans, with structural safeguards against writes.

Enables unified code search and analysis over a monorepo, combining exact, semantic, and call graph queries with indexing, incremental updates, and impact analysis.