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

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

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.

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

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

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

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

🧠 A high-performance PostgreSQL-backed MCP server acting as a super memory, task tracker, and dynamic database manager for AI agents. Features built-in connection pooling, a professional tasks schema, and a unique shared multi-agent coordination hub to prevent coding conflicts in real-time.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

An MCP server that provides real-time weather alerts, forecasts, stock market data, and news information through various API integrations.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

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.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

Local-first supply-chain CVE scanner. Scans project deps, system packages (Homebrew/apt), and IDE extensions (VS Code, JetBrains) via OSV, NVD, GHSA, EPSS, and CISA KEV. Listed in the official MCP Registry as io.github.DevInder1/tridentchain-security.

Enables AI agents to start, control, and verify local open.mp/SA-MP game servers via MCP stdio, using a headless RakClient to send allowed slash commands and assert round-trip responses.