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    Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.
    1
    MIT
  • A
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    Long-term memory for Claude Desktop and Claude Code over plain markdown files on your machine. It returns nothing when the corpus has no answer, naming the terms that appear nowhere — no least-bad match dressed as an answer. And it verifies cited commit SHAs against git, so an agent can tell what actually shipped from what was only discussed and abandoned. Local; nothing is transmitted.
    2
    114 npm
    MIT
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    Lets an agent delegate coding tasks and reviews to Claude Code, Codex or Grok Build CLIs running locally in isolated git worktrees, then poll an inbox for the status, question or final answer. Each caller sees only its own threads.
    21 npm
    MIT
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    Enables a chat or voice assistant to drive coding agents running in herdr: it can start an agent on a task, list and watch sessions started anywhere, send follow-ups, answer an agent's questions and approve or refuse its permission prompts. Long-running work is reported back through webhook callbacks so the conversation can continue without blocking.
    MIT
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    Connects MCP clients such as Claude, Cursor, and VS Code to OpenCode's headless API so users can ask questions, start and monitor background coding jobs, answer prompts and permission requests, and review changes across projects. It also exposes setup, model selection, job recovery, and configuration tools, along with resources and prompts, for multi-project workflows.
    24,321 npm
    MIT
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    Enables coding agents to discover projects, models, and sessions on an existing OpenCode server; delegate and supervise tasks; inspect progress, tool results, and diffs; answer authorized permission requests; and interrupt or redirect work via MCP or a JSON CLI.
    MIT
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    Connects MCP clients such as Claude, Cursor, and VS Code to OpenCode’s headless API so users can delegate coding tasks, monitor background jobs, answer prompts and permissions, and review changes across projects.
    24,321 npm
    MIT
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    Connects MCP clients such as Claude, Cursor, and VS Code to OpenCode's headless API so users can ask questions, implement features, run background coding jobs, answer permission and question prompts, and review changes across multiple projects. It also exposes project-aware resources, prompts, and job monitoring tools with configurable provider and model defaults.
    24,321 npm
    MIT
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    Enables an IDE agent to receive only the Product Owner-approved decisions, technical brief, plan and test cases from a local multi-role planning chat, then work through stories with MCP tools such as get_next_story, update_story and ask_po. Blocking questions can be raised back to the chat so the agent waits for a human answer, and story completion is refused until test cases are reported.
    Apache 2.0
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    Connects MCP clients such as Claude, Cursor, and VS Code to OpenCode's headless API so they can ask coding questions, implement features, run and monitor background jobs, answer prompts and permission requests, and review changes across multiple projects. Supports setup, provider/model selection, job recovery, and structured results with configurable tool profiles.
    24,321 npm
    MIT
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    Enables an MCP host to delegate a task to a fresh headless DeepSeek Harness agent that inherits the user's skills, AGENTS.md, and sign-in, runs one turn in a specified project directory, and returns the answer without a resident daemon. Supports long-running tasks via task ids for later collection, plus status, continue, and cancel tools.
    MIT
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    Connects MCP clients such as Claude, Cursor, and VS Code to OpenCode's headless API so users can delegate coding work, ask questions, implement features, and run jobs in the background. It also lets clients monitor job status, answer prompts and permission requests, and review changes across multiple projects.
    24,321 npm
    MIT
  • A
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    Two AIs. One answer. ChatGPT and Claude discuss with each other until they agree, through your own signed-in CLIs: no API keys. Both read your project (never change it) and search the web. Plugin for Claude Code, Codex, Claude Desktop and the ChatGPT app.
    2
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    2,269 npm
    5
    MIT
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    Get a second opinion on your code from every coding agent you have. Claude Code, Codex and Grok review each other's diffs and answer each other's questions, even inside a session that's already running. Uses the CLIs you're signed in to, no API keys.
    4
    1,196 npm
    1
    MIT
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    Bridges MCP clients such as Claude Code and Cursor to independent Codex app-server sessions, letting them start, poll, steer, review, compact, cancel, and answer prompts for asynchronous Codex tasks over local stdio or a remote authenticated WebSocket. Runs read-only by default, with workspace-write sandboxing only when a user explicitly enables it, and reports job status, model listing, and progress back to the client.
    10
    24 npm
    1
    MIT
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    Enables an AI coding agent to work through a fixed seven-phase cycle with enforced reflection gates and artifacts instead of jumping straight to code. Supports persistent tiered project memory with confidence decay, task analysis and routing, multi-model answer merging, and pattern-based safety warnings, while keeping cycle state on disk so a new chat can resume where the last one stopped.
    38
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    Apache 2.0
  • A
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    Connects MCP clients such as Claude, Cursor, and VS Code to an OpenCode server's headless API, enabling users to ask questions, delegate and run coding tasks, monitor background jobs, answer prompts and permission requests, and review resulting changes across multiple projects. Sessions accept absolute server-side project directories, support both blocking and asynchronous workflows, and expose persisted job records for recovering or cancelling work.
    24,321 npm
    MIT
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    Lets any MCP-capable coding harness (Cursor, Claude Code, Codex, Gemini CLI, VS Code/Copilot, opencode, and others) hand a self-contained task to a real, isolated DeepSeek Harness process that works in a chosen workspace with its own context window, model, and toolchain, then returns the final answer. Exposes task submission with time estimates and acceptance criteria, status polling with live progress and process-tree telemetry, graceful cancel and forced kill of whole process trees, and a health probe reporting concurrency, deadlines, and recent jobs.
    MIT