"Open-Source MCP Server in Python with PostgreSQL and OAuth 2.0" matching MCP servers:

Full-featured MCP server that exposes 36 tools for interacting with PostgreSQL databases, covering schema introspection, query execution, data exploration, performance monitoring, security auditing, and maintenance.

Enables AI agents to interact with PostgreSQL databases over HTTP/JSON-RPC, supporting SQL queries, schema introspection, table/index analysis, EXPLAIN query planning, role and privilege inspection, and database monitoring.

A production-ready MCP OAuth 2.1 server implementation with analytics and security monitoring, enabling secure authentication for MCP clients like Claude Desktop and Cursor.

Enables comprehensive PostgreSQL database monitoring, analysis, and management through natural language queries. Provides performance insights, bloat analysis, vacuum monitoring, and intelligent maintenance recommendations across PostgreSQL versions 12-17.

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.

Deterministic agentic data firewall that secures, monitors, and controls AI agent interactions with data and software via MCP, preventing data leaks.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

A Model Context Protocol (MCP) server for comprehensive monitoring and observability of systems using Langfuse.

Enables comprehensive NIST Cybersecurity Framework 2.0 assessments with 40+ MCP tools for maturity scoring, gap analysis, implementation planning, risk assessment, and executive reporting across 740 security questions.

A Python-based MCP server and React dashboard designed for system monitoring and automated notifications via PushPlus and Notion. It enables users to deploy a secure heartbeat tracking system with real-time updates through SSE.

Enables real-time data streaming through Server-Sent Events with timestamp broadcasting and server monitoring capabilities. Optimized for deployment on Render.com with health checks and status endpoints.

Multi-machine system monitor with a built-in MCP server that enables AI agents to query health metrics, manage processes, schedule cron jobs, and run diagnostics across local and remote machines.

Enables natural language queries for device support, including resolving device references, retrieving device details, historical metrics, and checking provisioning status. Maintains conversation context for multi-turn interactions.

Enables analysis of AI agent traces to detect and fix failures using heuristic detectors, with no LLM calls required.

Provides tools for obtaining system CPU and memory statistics through FastAPI endpoints exposed via MCP.

Enables state-aware Terraform/OpenTofu plan evaluation against live AWS topology and CloudWatch telemetry, detecting reliability blast radius and FinOps waste before merge.

Enables MCP clients to interact with ServiceNow instances for IT service management, CMDB, ITOM, and other domains via a governed skill catalog and runtime that enforces ACLs, business rules, and data policies.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

A GCP-hosted MCP server for Google Analytics GA4 where each user logs in with their own Google account and queries are scoped to that user's permissions.