"AWS Agent for Interacting with Multiple AWS Services" matching MCP servers:

An MCP server for managing AWS ECS clusters, services, tasks, and container logs. Enables AI assistants to perform operations like scaling, deployments, and log retrieval via natural language.

A Model Context Protocol server that integrates with AWS CodePipeline, allowing users to manage pipelines through Windsurf and Cascade using natural language commands.

A boilerplate TypeScript MCP server with Express.js designed for AWS AppRunner deployment. Provides sample tools, resources, and prompts with Docker containerization and GitHub Actions CI/CD workflow.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

Turns any AI coding agent or MCP client into a governed DevOps engineer by exposing policy-enforced tools for Kubernetes, Docker, Jira, Git/PR, CI/CD, AWS, Terraform, and incident response, with approvals, audit logging, secret redaction, and rollback enforced outside the model.

Enables recording of live LLM HTTP/SSE token streams and MCP stdio interactions into deterministic cassettes, then replaying them offline in CI in ~0ms with no network calls or API keys. Normalizes volatile headers, hashes prompts and tool calls, and scrubs secrets while enforcing SSRF and path-containment safeguards.

A read-only MCP server that lets agents scan a project's AI agent setup — Claude Code, Codex, Cursor, MCP servers and instruction files — and surface security findings such as the lethal trifecta, broad permissions, exposed secrets and unpinned packages.

Serves MCP tools to inspect agent trace JSONL files and evaluate them against golden-case constraints, returning structured metrics and gate results.

Enables interaction with Azure DevOps through natural language in Cursor IDE. Supports work item management, pull requests, builds, releases, test management, and guided workflows for development teams, QA testers, and release management.

Automates backporting upstream Ironic changes across OpenShift release branches using Claude AI for intelligent decision-making and natural language interaction.

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

Verify-before-act safety tools for AI coding agents, providing MCP tools to check packages, lockfiles, manifests, and CI workflows for supply chain risks.

Enables AI agents to safely automate Vivado build flows through state-aware MCP tools, asynchronous job tracking, and readiness gates for synthesis, implementation, and bitstream generation.

Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.

Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.

Integrates Cline with Azure DevOps services, enabling access to work items, repositories, and pull requests through configurable MCP tools.

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.

An MCP-style stdio server for evaluating AI agent outputs, enabling CI-friendly quality gates, regression comparisons, and canary promotion decisions.

Provides AI assistants with comprehensive access to Azure DevOps services including work items, repositories, pull requests, wikis, builds, pipelines, and test plans through 25+ MCP tools with multi-project support.

A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.