A drop-in Model Context Protocol (MCP) server that lets an AI agent query PostgreSQL — read-only, enforced at the database level, with real SQL validation, timeouts, cost limits, OAuth 2.1, and an audit trail.
A Model Context Protocol (MCP) server for PostgreSQL that provides safe, structured access to your database for AI assistants, enabling health checks, index tuning, lock analysis, and more.
A Model Context Protocol server that provides secure database access to PostgreSQL through Kysely ORM, enabling natural language interaction with PostgreSQL databases. It offers 40+ MCP tools for querying, schema inspection, diagnostics, and Java backend monitoring.
Read-only PostgreSQL analytics MCP server — query plans, slow queries, index usage, table bloat, vacuum status. No DDL/DML/writes. Curated by Archimedes Market with a verified Trust Report.
Enables AI assistants to manage, monitor, and optimize PostgreSQL databases with over 200 specialized tools for operations, security, performance tuning, and diagnostics.
The policy enforcement plane for MCP: deterministic admission and egress policy, attributable audit, and SIEM export for your MCP server fleet. Self-hosted and MIT licensed.
An MCP server that emits OpenTelemetry traces, metrics, and logs to OTLP endpoints in various formats. It includes tool-mimicry profiles to generate realistic traffic resembling common tools like nginx, postgres, and AWS Lambda for testing and demonstration purposes.
Enables AI assistants to interact with and manage Google Cloud Platform resources including Compute Engine, Cloud Run, Storage, BigQuery, and other GCP services through a standardized MCP interface.
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 comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.
MCP server for the Production Master incident-investigation service, enabling any MCP client to drive investigations via tool calls with pass-through authentication.
Enables querying and analyzing distributed traces from Jaeger, including service discovery, trace inspection, and performance analysis, through MCP tools.