"Non-Docker Implementation of Jira with MCP" matching MCP servers:

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

MCP server to provide Jira Tickets information to AI coding agents like Cursor

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

Enables Codex to delegate review and implementation tasks to the local Qoder CN CLI as background jobs, with two permission tiers and polling-based status updates.

An MCP server that splits coding work between ChatGPT web (planning, review) and Codex CLI (implementation), enabling agentic workflows over a local repo with risk-gated execution and safety rails.

A stdio MCP server that lets Codex Desktop/CLI delegate implementation tasks to Claude Code CLI with workspace validation, Git status checks, and session resume capabilities.

Exposes the local Claude Code CLI as a subagent for Codex, enabling background review and implementation jobs with two fixed permission tiers.

An MCP bridge that enables AI coding agents to delegate implementation tasks to the OpenAI Codex CLI, allowing the orchestrator to plan and review while Codex executes.

An MCP server that lets Claude spawn Cursor subagents as async, bounded workers, enabling non-blocking task delegation with asynchronous completion notifications.

Official implementation of Anthropic's 'think' tool that provides Claude with a dedicated space for structured reasoning, improving performance by up to 54% on complex tasks requiring multi-step problem solving.

Provides unified access to multiple CLI AI agents (Codex, Gemini, Claude, and OpenCode) through a single MCP interface with real-time task monitoring, enabling specialized code analysis, UI design, implementation, and prototyping workflows.

Connects AI coding assistants to Roblox Studio, enabling direct manipulation of the DataModel through natural language commands with undo support.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

A centralized MCP hub for managing multiple coding agents across projects, enabling parallel, non-blocking dispatch and orchestration from any MCP-capable client.

Enables MCP clients to run non-interactive Codex CLI sessions via codex and codex-reply tools, including resuming conversations by thread ID and passing codex exec flags.

Enables Claude Code and OpenAI Codex CLI to act as bidirectional partners by letting each ask the other for code review, explanations, planning, performance analysis, and implementation help. It also provides background job tools for starting, observing, waiting on, and cancelling delegated tasks.

Streamlines development workflows through AI-assisted codebase analysis, comprehensive planning, task breakdown with dependencies, and automated implementation verification. Enables systematic approach to complex development tasks like framework migrations and feature implementation.

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.