"Creating a Framework Design in Draw.io" matching MCP servers:

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

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.

Verifies AI agent completion claims by checking that claimed output files exist and are fresh, acting as a lightweight physical telemetry gate.

Supply-chain gate for AI agent skills and MCP servers: poison-scan tool definitions, hash-pin the vetted set into a lock file and verify drift in CI. truecopy-mcp is a drop-in stdio proxy that filters a live server's tools/list down to its pinned, unmodified, unpoisoned tools.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

Security auditor for CI ecosystems that detects supply-chain and injection flaws in CI/CD configuration files across seven CI platforms, providing taint analysis, remediation, and compliance scoring.

MCP server with the watch_ci tool that polls GitHub Actions until a commit's CI run finishes, then returns the outcome and failed log tail in one call.

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

Provides MCP tools to get a single-call snapshot of git and GitHub Actions CI status across all repositories in a folder, flag missing or stale architecture docs, write doc files, and detect release drift between source and release repositories.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps services, allowing users to query work items with plans to support creating/updating items, managing pipelines, handling pull requests, and administering sprints and branch policies.

Publishes normalized release notices to a configured webhook via MCP, with built-in validation, deterministic dry-run mode, and a clear boundary for authority gates.

Enables AI coding agents to retrieve the latest stable versions of packages and tools across multiple ecosystems, preventing outdated dependency versions in generated code.

A CircleCI MCP server specialized in config review, providing tools for fetching actual configs, validating changes, and analyzing workflow bottlenecks, health, and DAG dependencies.

Enables Claude to run structured software development pipelines by directing it through sequential phases, validating evidence before advancing, and persisting state in SQLite for resumption across sessions.

Enables AI assistants to manage website deployments over SFTP/FTPS by listing sites, testing connections, comparing files, previewing changes with approval tokens, creating SHA-256 verified backups, and executing authorized uploads.

Publishes static sites to Drop2Run from an AI agent: hand it files written in the chat or a folder on disk, and it returns a live HTTPS URL. Six tools — publish_files, publish_dir, list_sites, delete_site, and login / login_code — with no git, no build step and no repository.

Scaffold and audit Starter Series projects — MCP server, Claude Code skill, and CLI in one package.

Validates release hygiene in local repositories with network-free, read-only tools for checking repo structure, version alignment, and generating release checklists.