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

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Exposes open automation platform capabilities to AI agents with tools for managing job templates, inventories, collections, EDA activations, audit events, and policy checks, governed by gateway auth, RBAC, and policy enforcement.

provides AI-powered PostgreSQL performance tuning capabilities.

A DevOps-friendly template for building MCP servers with CI/CD, Docker support, and automatic documentation generation using fastmcp and FastAPI.

Enables automated Python code quality checks including linting, complexity analysis, typo detection, structure validation, duplicate detection, and test coverage, with integration into Cursor IDE and CLI.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

Enables interaction with Azure DevOps services through Personal Access Token authentication. Provides 75 tools for managing work items, builds, repositories, pull requests, and other DevOps operations via both CLI and HTTP API interfaces.

Enables agents to run configured JSON equality checks and assigned pinned GitHub checks through a local stdio connector with operator-provisioned API access. It helps verify disclosed automation evidence against explicit check scopes.

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

Integrates GitLab with AI assistants to manage merge requests, analyze CI/CD pipelines, and create Architecture Decision Records. It enables seamless code searching, pipeline triggering, and deployment management through the Model Context Protocol.

An open source MCP server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments.

A production-ready template for building Model Context Protocol servers in Python, featuring example tools, structured logging, and multiple transport protocols.

Read-only MCP server for VecheMoga, enabling AI assistants to query PostgreSQL, inspect logs, and check API delivery status.

Self-hosted, multi-zone MCP server for GKE/EKS: git repo of Python tools → canary-deployed Rust+Python workers, OAuth sign-in, roles per group.

Enables AI agents to deploy static files and get live HTTPS URLs instantly, with support for custom domains and data residency.

Enables AI coding tools to scaffold, build, and deploy Node.js or Python apps to Varity with a single command, automatically provisioning databases and backend services.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

MCP server for MongoDB's Evergreen CI/CD platform, enabling AI assistants to manage projects, analyze builds, and troubleshoot failures via natural language.