"Information about CAD (Computer-Aided Design)" matching MCP servers:

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.

Aegis keeps Claude Code, Codex CLI and Antigravity on your project's rules via a zero-dependency Model Context Protocol (MCP) server (aegis-mcp), AGENTS.md / CLAUDE.md bootstrap, git pre-commit hooks, and CI governance (aegis check). It serves each agent just-in-time rules for the files it is about to edit, then enforces AST and repository invariants before commit and in pull requests.

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

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Enables AI assistants to answer questions about nixpkgs packages using nixkeeper's public data, covering outdated versions, Hydra build status and failures, update-bot attempts, related PRs and issues, CVEs, and what needs attention for a maintainer or team. It runs locally over stdio, reads only public data, and requires no account or token.

Enables retrieving comprehensive information about GitLab merge requests, including details, commits, diffs, discussions, approvals, and CI/CD status, through natural language.

A git-native merge gate. mergelock check compares two branches before they meet and reports the conflicts git itself won't tell you about: a function whose signature changed on one branch while the other branch added calls to the old signature, a symbol deleted on one side but still used on the other, the same function written twice.

An MCP server implementing a 7-stage agentic frontend workflow—from design audit to PR review—including AI-driven component generation, browser validation, E2E testing, and CI self-healing.

Enables interaction with the Tembo API to manage organization tasks and view enabled code repositories. Users can create, search, and list tasks or retrieve account information directly through MCP-compatible clients.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

Enables interaction with Blacksmith CI analytics to query workflow runs, jobs, test results, and usage metrics. It provides detailed access to CI/CD data including job logs and billing information directly through Claude.

Automates GitHub issue-to-PR workflows using specialized AI agents (analyst, architect, developer, tester, reviewer) that analyze requirements, design solutions, implement code, generate tests, and perform code reviews with HIPAA compliance checks.

A Model Context Protocol server that allows management of Netlify sites, enabling users to create, list, get information about, and delete Netlify sites directly from an MCP-enabled environment.

A Model Context Protocol server that enables integration with GitHub Actions, allowing users to fetch available actions, get detailed information about specific actions, trigger workflow dispatch events, and fetch repository releases.

Enables AI assistants to interact with Terraform Cloud workspaces and runs, including checking run status, listing workspaces, and retrieving detailed information about workspaces and runs.

Give your coding agent the dependency graph it is about to change: scan, diff, explain, audit.

Enables automated analysis of Woodpecker CI pipeline failures with intelligent error detection and fix suggestions. Supports both direct pipeline analysis and IDE-integrated git-context analysis using repository names, PR numbers, or branch information.

Full-coverage GitLab MCP server with 44 tools across 18 resource types. Agent-optimized CQRS design — one tool call handles complete multi-step operations. Supports OAuth 2.1, read-only mode, stdio/SSE/StreamableHTTP transports, and GraphQL-native work items with full hierarchy (epics,issues,etc)

Enables AI assistants to list and retrieve repositories, fetch and create pull requests, and access pipeline information through cloud and server APIs with configurable authentication.