"Adding web browsing and page reading capabilities to an agent" matching MCP servers:

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

Local MCP server bridging ChatGPT Web to local tools for file, shell, git, test, and process management with secure policy controls.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Exposes an authenticated local runtime over OpenAI Tunnel so ChatGPT can inspect authorized Windows workspaces, read bounded Git status and diffs, submit and cancel Codex CLI tasks, and use workspace Skills. It also brokers connections to optional loopback stdio or HTTP MCP services, such as Stata and Zotero, with explicit tool allowlists and loopback-only access.

A filesystem-based MCP server for AI coding agents to coordinate work across git worktrees by claiming files, checking for conflicts, and logging progress without affecting the repository's git history.

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

Exposes GitHub issue and pull-request triage capabilities to any MCP client: fetching repository context, classifying and prioritizing requests, finding duplicates, and applying labels, comments, assignments, closures, or reopenings. All writes are policy-gated, dry-run by default, and destructive actions require explicit two-step human confirmation.

MCP server that spawns autonomous Claude Code agents in GitHub repos, enabling task delegation with persistent state, multi-step workflows, and job monitoring.

MCP Server for Git operations, agent templates, and project utilities.

Provides an MCP control plane for a dedicated Linux VM, enabling shell-equivalent command execution, bounded filesystem and Git workspace operations, persistent process and coding-agent orchestration, artifact presentation, and optional upstream MCP bridge re-exports.

mcp-agent-ops is a local stdio MCP server for deterministic agent-development operations that otherwise cause repeated shell and generated Python calls.

An MCP execution layer that lets capable AI models safely control a developer workstation for file edits, terminal and process execution, Git operations, language-server analysis, browser and Windows UI automation, media processing, job/resource control, and checkpointing. It also coordinates durable single- or multi-agent tasks across providers with leases, dependency graphs, evidence logs, repair loops, and separate verification gates.

An OpenAI-powered developer intelligence MCP server that scans GitHub repositories, extracts and clusters agent engineering patterns, analyzes local codebases, and proposes safe AGENTS.md improvements.

Enables people and their AI agents to share a kanban board whose tasks, hand-offs, reviews, notes and alerts live as markdown files in a private GitHub repo, with per-person access control. Works from Claude, ChatGPT, Claude Code, Codex or any MCP-speaking client, and can draw the board inside chats.

A coordination layer for parallel coding agents that provides intent-carrying claims, conflict prediction, and a serialized landing queue to prevent merge conflicts.

MCP server that guides an AI agent through stack trace triage, from raw error to the commit and PR that introduced it.

Lets an AI coding agent journal its edits, commands, checkpoints, intents and test evidence locally, then compile them into a machine-readable Change Package plus a human-readable review summary with statically computed risks. Optionally publishes the result as a GitHub Draft PR with inline comments on the exact diff lines, always gated behind explicit confirmation and redaction.

An AI-powered code review agent that leverages Model Context Protocol (MCP) and Claude to provide intelligent, context-aware code reviews.

Provides a restricted Docker-based sandbox for LLM agents, enabling file operations, command execution, and local Git within an isolated runtime.

Enables searching GitHub repositories, fetching readable web page text, and querying a local book database through MCP tool calls.