"Collaboration and Documentation Platform by Atlassian" matching MCP servers:

A multi-agent collaborative development bridge that enables TRAE Work to offload complex tasks to Codex executor, with tools for task submission, status tracking, artifact listing, and permission management.

MCP server that enables AI agents to analyze legacy code, plan and execute software migrations, generate modern source code, and validate production-ready artifacts through a multi-agent pipeline.

An interactive coding agent and MCP server that provides access to various AI models via the Tsinghua University lab proxy API. It enables users to inspect files and execute shell commands within their local directory using models like DeepSeek, GLM, and Qwen.

Orchestrates multiple Claude Code agents across iTerm2 sessions with process-level isolation, enabling collaborative AI development workflows on multiple codebases with task-based inter-agent communication and persistent state management.

Bridges Warp's Oz coding agent to any IDE or MCP client (Claude Code, Cursor, Codex), plus native @oz in VS Code Copilot Chat. Cross-platform (macOS/Linux/Windows), independent project using only Warp's documented public oz CLI + MCP interfaces.

Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

Enables AI tools to interact with browsers for enhanced frontend development, providing context to LLMs through tools like API call analysis, screenshots, element selection, and documentation ingestion.

MCP server for bidirectional AI agent collaboration — 5 tools for spawning and communicating with any agent CLI

An MCP (Model Context Protocol) server that enables integration with the Simplifier Low Code Platform. This server provides tools and capabilities for creating and managing Simplifier Connectors and BusinessObjects through the platform's REST API.

MCP server that provides AI coding agents automatic access to AGENTS.md documentation from GitHub repositories, enabling understanding of codebase conventions and patterns.

A cross-platform MCP server implementing the Ralph Loop iterative development technique where a worker model does the work and a reviewer model provides cross-model review until approval.

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.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

Enables collaboration between multiple AI models (GPT, Claude, Gemini) to work together on complex tasks, with intelligent task distribution and role-based expert assignment for code development, review, and optimization.

An MCP server that enables Claude and other LLM clients to access Hanzo AI platform capabilities and provide powerful code management tools for analyzing, modifying, and understanding projects.

Integrates with Dispersl to provide multi-agent orchestration for AI-driven software development, enabling code generation, testing, documentation, git operations, and chat.

An MCP server that implements a structured workflow for LLM-based coding, guiding development through feature clarification, documentation generation, phased implementation, and progress tracking.

Enables Claude Code as a team leader to delegate tasks to GPT and Gemini experts, supporting multi-LLM collaboration with tools for consultation, code review, design, and background execution.

Enables agents to generate typed client code from OpenAPI, GraphQL, Protobuf, and SQL specs using MetaEngine's code-generation platform.

Enables finding existing shadcn-format UI components by plain-language description instead of exact names, returning ranked matches with install commands and per-dimension match reasons.

Enables multiple AI coding agents to collaborate on a project by coordinating tasks, file leases, and messages through a shared hub, preventing conflicts and enabling parallel development.

Enables users to run reusable Markdown-defined coding agents from any MCP-compatible client, delegating tasks such as code review, test writing, investigation, and documentation to a chosen coding CLI backend and returning results to the same conversation.

Enables MCP-capable assistants to build, preview, and publish full-stack web apps by directing a hosted coding agent, with tools for projects, wallet balance, domains, previews, downloads, and GitHub export.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

Provides AI coding agents with access to CleanSlice architecture documentation, rules, and conventions. It enables users to search documentation and retrieve essential patterns to help AI build applications correctly.

Enables coding agents to control other application windows by providing primitives for clicking, typing, capturing screenshots, and window management. Supports macOS, Windows, and Linux.

Enables two-way collaboration between Claude Code and the Codex CLI: Claude can hand off plans for execution or adversarial review, while the working agent can block to ask Claude questions, report progress or findings, and receive mid-run corrections. Supports multiple named, resumable sessions per project with configurable model, effort, and sandbox settings.

A project intelligence platform for AI coding agents that scans, audits, generates, and monitors context files (CLAUDE.md, AGENTS.md, etc.) with drift detection and repair capabilities.

dev-brain-mcp

Lets MCP-compatible clients run reusable Markdown-defined coding agents with a chosen backend CLI and return their results to the same conversation. It supports delegating tasks such as code review, test writing, investigation, and documentation, with shared settings and optional session continuation.

Indexes GitHub repositories and provides living documentation context to coding agents, enabling them to ground work in actual repository conventions and propose doc updates.

Provides token-efficient code retrieval for coding agents by indexing repositories and enabling ranked snippet search, symbol outlines, and surgical line reads.

Enables MCP clients to spawn and manage collaboration-style external subagents with persistent sessions, queued messaging, nested delegation limits, and shared budget/concurrency controls, plus a bilingual Windows desktop control UI.

It lets MCP-compatible clients run reusable Markdown-defined coding agents for tasks such as code review, test writing, investigation, and documentation through a chosen coding CLI backend, with optional model, permission, and session continuation settings.

Enables AI agents to browse, create, and manage apps on the FreeAppStore platform, including provisioning repositories, writing code, and deploying live.

Enables quota-aware multi-agent orchestration for OpenCode and Codex by separating manager/reviewer roles from worker agents, rotating Google Antigravity CLI and Chrome CDP Gemini Web accounts, and delegating heavy code generation, refactoring, testing, and documentation to zero-cost workers.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

Let your memories live forever by passing your knowledge to the next generation with SelfMemory.

Enables STDIO-compatible AI assistants to queue coding work onto the official Google Antigravity CLI and track status, read reports or patches, query capabilities, or cancel running tasks without blocking. Supports trusted direct execution plus optional isolated or read-only modes depending on the platform.

Coordinates parallel AI coding agents by providing task ownership, scoped file locks, handoffs, and verification workflows.