"Automating browser tasks to pull data" matching MCP servers:

A comprehensive and efficient Model Context Protocol server for task management that works with Claude, Cursor, and other MCP clients, providing powerful search, filtering, and organization capabilities across multiple file formats.

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.

Analyzes Git pull request diffs to detect breaking REST and GraphQL API schema changes, providing deterministic AST-level code review and breaking change alerts for CI/CD workflows.

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

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

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

Enables developers to manage Genesys Cloud Function Data Actions through natural language in Cursor, including validating, building, planning, and applying function deployments while enforcing safety controls like plan-before-apply and read-only mode.

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.

Enables inspecting local Git repositories and automating delivery tasks such as status checks, diffs, commits, pull requests, and deployments using git and GitHub CLI.

MCP aggregator with many existing NCP templates and allows running external MCP servers too

Generates a daily standup note from GitLab merge request or GitHub pull request state: what is ready to merge, what is blocked, what is stale, and what is waiting on your review. When CI is red it opens the failed job's log and reports the error lines, so the note says why the pipeline failed rather than just that it did.

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.

Enables coding agents to read Squally CI data, including test results, flakiness, and failure diagnostics.

Enables AI agents to deploy HTML and pull reviewer comments via the briefroom CLI without spawning shells.

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

MCP server for auditable repository self-maintenance, turning GitHub issues and failed CI into independently verified pull requests with full audit trails, human approvals, and runbook archival.

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.

A Model Context Protocol server for Bitbucket Cloud that lets agents read pull request diffs, comments, and pipeline logs, as well as write PR comments and edit PR details.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.