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claude-teamClaude team 搜索

Agent Skill

claude-team 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

95

周安装

4

GitHub Stars

177

下载量

33
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:claude-team(Claude team 搜索)
来源仓库:https://github.com/moltbot/skills
仓库路径:skills/claude-team
安装命令:
npx skills add moltbot/skills --skill "claude-team"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add moltbot/skills --skill "claude-team"

简介

使用 claude-team MCP 服务器通过 iTerm2 协调多个 Claude Code 工作人员。使用 git 工作树生成工作人员、分配珠子问题、监控进度并协调并行开发工作。

SKILL.md

name
claude-team
description
Orchestrate multiple Claude Code workers via iTerm2 using the claude-team MCP server. Spawn workers with git worktrees, assign beads issues, monitor progress, and coordinate parallel development work.
homepage
https://github.com/Martian-Engineering/claude-team
metadata
{"clawdbot":{"emoji":"👥","os":["darwin"],"requires":{"bins":["mcporter"]}}}

Claude Team

Claude-team is an MCP server that lets you spawn and manage teams of Claude Code sessions via iTerm2. Each worker gets their own terminal pane, optional git worktree, and can be assigned beads issues.

Why Use Claude Team?

  • Parallelism: Fan out work to multiple agents working simultaneously
  • Context isolation: Each worker has fresh context, keeps coordinator context clean
  • Visibility: Real Claude Code sessions you can watch, interrupt, or take over
  • Git worktrees: Each worker can have an isolated branch for their work

⚠️ Important Rule

NEVER make code changes directly. Always spawn workers for code changes. This keeps your context clean and provides proper git workflow with worktrees.

Prerequisites

  • macOS with iTerm2 (Python API enabled: Preferences → General → Magic → Enable Python API)
  • claude-team MCP server configured in ~/.claude.json

Using via mcporter

All tools are called through mcporter call claude-team.<tool>:

mcporter call claude-team.list_workers
mcporter call claude-team.spawn_workers workers='[{"project_path":"/path/to/repo","bead":"cp-123"}]'

Core Tools

spawn_workers

Create new Claude Code worker sessions.

mcporter call claude-team.spawn_workers \
  workers='[{
    "project_path": "/path/to/repo",
    "bead": "cp-123",
    "annotation": "Fix auth bug",
    "use_worktree": true,
    "skip_permissions": true
  }]' \
  layout="auto"

Worker config fields:

  • project_path: Required. Path to repo or "auto" (uses CLAUDE_TEAM_PROJECT_DIR)
  • bead: Optional beads issue ID — worker will follow beads workflow
  • annotation: Task description (shown on badge, used in branch name)
  • prompt: Additional instructions (if no bead, this is their assignment)
  • use_worktree: Create isolated git worktree (default: true)
  • skip_permissions: Start with --dangerously-skip-permissions (default: false)
  • name: Optional worker name override (auto-picks from themed sets otherwise)

Layout options:

  • "auto": Reuse existing claude-team windows, split into available space
  • "new": Always create fresh window (1-4 workers in grid layout)

list_workers

See all managed workers:

mcporter call claude-team.list_workers
mcporter call claude-team.list_workers status_filter="ready"

Status values: spawning, ready, busy, closed

message_workers

Send messages to one or more workers:

mcporter call claude-team.message_workers \
  session_ids='["Groucho"]' \
  message="Please also add unit tests" \
  wait_mode="none"

wait_mode options:

  • "none": Fire and forget (default)
  • "any": Return when any worker is idle
  • "all": Return when all workers are idle

check_idle_workers / wait_idle_workers

Check or wait for workers to finish:

# Quick poll
mcporter call claude-team.check_idle_workers session_ids='["Groucho","Harpo"]'

# Blocking wait
mcporter call claude-team.wait_idle_workers \
  session_ids='["Groucho","Harpo"]' \
  mode="all" \
  timeout=600

read_worker_logs

Get conversation history:

mcporter call claude-team.read_worker_logs \
  session_id="Groucho" \
  pages=2

examine_worker

Get detailed status including conversation stats:

mcporter call claude-team.examine_worker session_id="Groucho"

close_workers

Terminate workers when done:

mcporter call claude-team.close_workers session_ids='["Groucho","Harpo"]'

⚠️ Worktree cleanup: Workers with worktrees commit to ephemeral branches. After closing:

  1. Review commits on the worker's branch
  2. Merge or cherry-pick to a persistent branch
  3. Delete the branch: git branch -D <branch-name>

bd_help

Quick reference for beads commands:

mcporter call claude-team.bd_help

Worker Identification

Workers can be referenced by any of:

  • Internal ID: Short hex string (e.g., 3962c5c4)
  • Terminal ID: iterm:UUID format
  • Worker name: Human-friendly name (e.g., Groucho, Aragorn)

Workflow: Assigning a Beads Issue

# 1. Spawn worker with a bead assignment
mcporter call claude-team.spawn_workers \
  workers='[{
    "project_path": "/Users/phaedrus/Projects/myrepo",
    "bead": "proj-abc",
    "annotation": "Implement config schemas",
    "use_worktree": true,
    "skip_permissions": true
  }]'

# 2. Worker automatically:
#    - Creates worktree with branch named after bead
#    - Runs `bd show proj-abc` to understand the task
#    - Marks issue in_progress
#    - Implements the work
#    - Closes the issue
#    - Commits with issue reference

# 3. Monitor progress
mcporter call claude-team.check_idle_workers session_ids='["Groucho"]'
mcporter call claude-team.read_worker_logs session_id="Groucho"

# 4. When done, close and merge
mcporter call claude-team.close_workers session_ids='["Groucho"]'
# Then: git merge or cherry-pick from worker's branch

Workflow: Parallel Fan-Out

# Spawn multiple workers for parallel tasks
mcporter call claude-team.spawn_workers \
  workers='[
    {"project_path": "auto", "bead": "cp-123", "annotation": "Auth module"},
    {"project_path": "auto", "bead": "cp-124", "annotation": "API routes"},
    {"project_path": "auto", "bead": "cp-125", "annotation": "Unit tests"}
  ]' \
  layout="new"

# Wait for all to complete
mcporter call claude-team.wait_idle_workers \
  session_ids='["Groucho","Harpo","Chico"]' \
  mode="all"

# Review and close
mcporter call claude-team.close_workers \
  session_ids='["Groucho","Harpo","Chico"]'

Best Practices

  1. Use beads: Assign bead IDs so workers follow proper issue workflow
  2. Use worktrees: Keeps work isolated, enables parallel commits
  3. Skip permissions: Workers need skip_permissions: true to write files
  4. Monitor, don't micromanage: Let workers complete, then review
  5. Merge carefully: Review worker branches before merging to main
  6. Close workers: Always close when done to clean up worktrees

HTTP Mode (Streamable HTTP Transport)

For persistent server operation, claude-team can run as an HTTP server. This keeps the MCP server running continuously with persistent state, avoiding cold starts.

Starting the HTTP Server

Run the claude-team HTTP server directly:

# From the claude-team directory
uv run python -m claude_team_mcp --http --port 8766

# Or specify the directory explicitly
uv run --directory /path/to/claude-team python -m claude_team_mcp --http --port 8766

For automatic startup on login, use launchd (see the "launchd Auto-Start" section below).

mcporter.json Configuration

Once the HTTP server is running, configure mcporter to connect to it. Create ~/.mcporter/mcporter.json:

{
  "mcpServers": {
    "claude-team": {
      "transport": "streamable-http",
      "url": "http://127.0.0.1:8766/mcp",
      "lifecycle": "keep-alive"
    }
  }
}

Benefits of HTTP Mode

  • Persistent state: Worker registry survives across CLI invocations
  • Faster responses: No Python environment startup on each call
  • External access: Can be accessed by cron jobs, scripts, or other tools
  • Session recovery: Server tracks sessions even if coordinator disconnects

Connecting from Claude Code

Update your .mcp.json to use HTTP transport:

{
  "mcpServers": {
    "claude-team": {
      "transport": "streamable-http",
      "url": "http://127.0.0.1:8766/mcp"
    }
  }
}

launchd Auto-Start

To automatically start the claude-team server on login, use the bundled setup script.

Quick Setup

Run the setup script from the skill's assets directory:

# From the skill directory
./assets/setup.sh

# Or specify a custom claude-team location
CLAUDE_TEAM_DIR=/path/to/claude-team ./assets/setup.sh

What the Setup Does

The setup script:

  1. Detects your uv installation path
  2. Creates the log directory at ~/.claude-team/logs/
  3. Generates a launchd plist from assets/com.claude-team.plist.template
  4. Installs it to ~/Library/LaunchAgents/com.claude-team.plist
  5. Loads the service to start immediately

The plist template uses uv run to start the HTTP server on port 8766, configured for iTerm2 Python API access (Aqua session type).

Managing the Service

# Stop the service
launchctl unload ~/Library/LaunchAgents/com.claude-team.plist

# Restart (re-run setup)
./assets/setup.sh

# Check if running
launchctl list | grep claude-team

# View logs
tail -f ~/.claude-team/logs/stdout.log
tail -f ~/.claude-team/logs/stderr.log

Troubleshooting launchd

# Check for load errors
launchctl print gui/$UID/com.claude-team

# Force restart
launchctl kickstart -k gui/$UID/com.claude-team

# Remove and reload (if plist changed)
launchctl bootout gui/$UID/com.claude-team
launchctl bootstrap gui/$UID ~/Library/LaunchAgents/com.claude-team.plist

Cron Integration

For background monitoring and notifications, claude-team supports cron-based worker tracking.

Worker Tracking File

Claude-team writes worker state to ~/.claude-team/memory/worker-tracking.json:

{
  "workers": {
    "Groucho": {
      "session_id": "3962c5c4",
      "bead": "cp-123",
      "annotation": "Fix auth bug",
      "status": "busy",
      "project_path": "/Users/phaedrus/Projects/myrepo",
      "started_at": "2025-01-05T10:30:00Z",
      "last_activity": "2025-01-05T11:45:00Z"
    },
    "Harpo": {
      "session_id": "a1b2c3d4",
      "bead": "cp-124",
      "annotation": "Add API routes",
      "status": "idle",
      "project_path": "/Users/phaedrus/Projects/myrepo",
      "started_at": "2025-01-05T10:30:00Z",
      "last_activity": "2025-01-05T11:50:00Z",
      "completed_at": "2025-01-05T11:50:00Z"
    }
  },
  "last_updated": "2025-01-05T11:50:00Z"
}

Cron Job for Monitoring Completions

Create a monitoring script at ~/.claude-team/scripts/check-workers.sh:

#!/bin/bash
# Check for completed workers and send notifications

TRACKING_FILE="$HOME/.claude-team/memory/worker-tracking.json"
NOTIFIED_FILE="$HOME/.claude-team/memory/notified-workers.json"
TELEGRAM_BOT_TOKEN="${TELEGRAM_BOT_TOKEN}"
TELEGRAM_CHAT_ID="${TELEGRAM_CHAT_ID}"

# Exit if tracking file doesn't exist
[ -f "$TRACKING_FILE" ] || exit 0

# Initialize notified file if needed
[ -f "$NOTIFIED_FILE" ] || echo '{"notified":[]}' > "$NOTIFIED_FILE"

# Find idle workers that haven't been notified
IDLE_WORKERS=$(jq -r '
  .workers | to_entries[] |
  select(.value.status == "idle") |
  .key
' "$TRACKING_FILE")

for worker in $IDLE_WORKERS; do
  # Check if already notified
  ALREADY_NOTIFIED=$(jq -r --arg w "$worker" '.notified | index($w) != null' "$NOTIFIED_FILE")

  if [ "$ALREADY_NOTIFIED" = "false" ]; then
    # Get worker details
    BEAD=$(jq -r --arg w "$worker" '.workers[$w].bead // "no-bead"' "$TRACKING_FILE")
    ANNOTATION=$(jq -r --arg w "$worker" '.workers[$w].annotation // "no annotation"' "$TRACKING_FILE")

    # Send Telegram notification
    MESSAGE="🤖 Worker *${worker}* completed
📋 Bead: \`${BEAD}\`
📝 ${ANNOTATION}"

    curl -s -X POST "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/sendMessage" \
      -d chat_id="$TELEGRAM_CHAT_ID" \
      -d text="$MESSAGE" \
      -d parse_mode="Markdown" > /dev/null

    # Mark as notified
    jq --arg w "$worker" '.notified += [$w]' "$NOTIFIED_FILE" > "${NOTIFIED_FILE}.tmp"
    mv "${NOTIFIED_FILE}.tmp" "$NOTIFIED_FILE"
  fi
done

Make it executable:

chmod +x ~/.claude-team/scripts/check-workers.sh

Crontab Entry

Add to crontab (crontab -e):

# Check claude-team workers every 2 minutes
*/2 * * * * TELEGRAM_BOT_TOKEN="your-bot-token" TELEGRAM_CHAT_ID="your-chat-id" ~/.claude-team/scripts/check-workers.sh

Environment Setup

Set Telegram credentials in your shell profile (~/.zshrc):

export TELEGRAM_BOT_TOKEN="123456789:ABCdefGHIjklMNOpqrsTUVwxyz"
export TELEGRAM_CHAT_ID="-1001234567890"

Alternative: Using clawdbot for Notifications

If you have clawdbot configured, you can send notifications through it instead:

# In check-workers.sh, replace the curl command with:
clawdbot send --to "$TELEGRAM_CHAT_ID" --message "$MESSAGE" --provider telegram

Clearing Notification State

When starting a fresh batch of workers, clear the notified list:

echo '{"notified":[]}' > ~/.claude-team/memory/notified-workers.json

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

openclaw

59.86%
按下载量换算20

Claude Code

29.3%
按下载量换算10

安全审计

暂无安全审计结果可展示。

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add moltbot/skills --skill "claude-team" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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