"browser use" matching MCP servers:

Exposes Registry Browser operations (embed, de-embed, publish, create packages) as MCP tools for AI agents and IDE integrations to manage Unity packages programmatically.

Provides read-only access to Azure DevOps using your browser session, no PAT required. Enables browsing projects, repos, work items, pull requests, and feeds through MCP tools.

Browser acceptance testing for AI agent deliverables: verify agent output in real Chromium from JSON specs, with MCP server, visual regression, multi-browser support and GitHub Actions.

This MCP server lets you use Cursor IDE, or any MCP Client enabled agent, to use natural language to accomplish things with CircleCI, e.g: Find the latest failed pipeline on my branch and get logs

A secure MCP server providing read-only access to Argo CD instances using browser session cookies, enabling querying of applications, projects, clusters, and repositories.

An MCP server that lets agents draw 18 diagram types from JSON (no SVG, no headless browser)

A local MCP server that bridges Claude Desktop/Cowork to the Azure DevOps CLI, enabling full use of az devops, az repos, az boards, az pipelines, and az artifacts commands.

Enforces authorize-before-execute for any MCP-compatible AI agent. Exposes atlasent_evaluate and atlasent_verify_permit tools so a protected tool call only runs after AtlaSent issues and verifies a signed, single-use permit — fail-closed on any error, timeout, or malformed response.

Enables test execution and management through MCP clients, allowing retrieval of projects, listing tests, executing tests with browser selection, and monitoring results.

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 headless Blender asset QA and FBX reimport verification for game and 3D asset pipelines, checking mesh count, material count, and naming prefixes with deterministic JSON results.

MCP-native release confidence control plane that turns browser execution into auditable go/no-go decisions by combining business-critical journey context, evidence-heavy QA runs, and risk governance.

Python MCP server for Selenium WebDriver — 84 tools for browser automation, element interactions, assertions, self-healing locators, and codegen for Java TestNG / JUnit 5 / Cucumber / pytest / C# NUnit / Playwright and CI pipelines (GitHub Actions / Jenkins / GitLab CI). No ChromeDriver setup needed.

Enables natural language management of Doppler secrets, projects, configs, and environments by wrapping the Doppler CLI for use with MCP clients like Claude Desktop.

SuperDev is a local-first desktop app + MCP server that gives AI coding agents (Claude Code, Codex, Cursor — anything MCP-compatible) access to the runtime: live and historical logs across services, breakpoints in already-running processes (same PID, no restart), real browser control, and DAG deploy pipelines — with human approval and an audit trail on protected writes.

MCP server for enforcing coding rules in Rust projects via scanning, routing, and explanation tools, designed for use with Codex, CI pipelines, and precommit hooks.

AI code reviews and git activity digests with machine-readable risk scoring, available as an MCP server for use within an agent session.

Enables evidence-first release readiness assessment by running or accepting build, API, browser, visual, performance, and security evidence, then returning SHIP, REVIEW, or HOLD recommendations with clustered regressions.

Once configured, you can use natural language commands like: "Search for failed builds in the last week" "Why last deploy was failed" "Search the most failed builds" "Trigger a build for the main branch" "Show me recent builds for project X" "Pin the latest successful build" "Cancel the running bui

A dual-track testing server that combines CLI test execution with Playwright-based browser testing and persistent SQLite logging. It enables automated test pipelines, Git integration, and evidence-based requirement generation to streamline the development lifecycle.