crewmail

crewmail

File-based MCP server for AI coding agents to coordinate via inbox messaging and human escalation.

Category
访问服务器

README

crewmail

Interoffice mail for your AI crew — a zero-dependency, file-based message bus and shared inbox for AI coding agents (Claude Code, Codex CLI, Cursor, ...) working on the same machine, with a built-in human escalation queue and an MCP server.

Why

Running multiple AI coding agents in parallel on one codebase is increasingly common, but coordination between them is usually ad hoc: tmux panes, comments left in code, or nothing at all. Agents overwrite each other's work, ask the same question twice, and block silently when they hit a decision only a human can make. crewmail gives agents a durable, auditable inbox instead: register, send, check mail, ack, and — when you're stuck on something only a human can decide — escalate and move on to other work.

Quick start

# In your project root
npx crewmail init

# Register two agents
npx crewmail register --code CLAUDE-01 --name "Claude Code" --runtime claude --role builder
npx crewmail register --code CODEX-01 --name "Codex CLI" --runtime codex --role implementer

# Claude asks Codex to do something
npx crewmail send --from CLAUDE-01 --to CODEX-01 --kind task \
  --subject "Implement rate limiter" --body "Add a token-bucket limiter to src/http/client.ts"

# Codex checks its inbox
npx crewmail inbox --agent CODEX-01

# Codex acknowledges it
npx crewmail ack --agent CODEX-01 --all

# Anyone can see who's around and what's outstanding
npx crewmail status

Data lives in .crewmail/ at your project root (created by init): an append-only mail.jsonl log, reads.jsonl read receipts, and a mutable agents.json registry. .crewmail/*.jsonl is gitignored by default; run crewmail init --commit-log if you want the audit trail checked into git instead.

The protocol

crewmail comes with a short, paste-into-your-AGENTS.md protocol snippet: docs/protocol.md. It covers session start, declaring work before touching shared files, escalating to a human, and reporting on completion.

Human escalation

Any message can be addressed to the reserved recipient HUMAN. Send one with --kind decision_request when an agent is blocked on something only a person can decide:

crewmail send --from CLAUDE-01 --to HUMAN --kind decision_request \
  --subject "Approve prod deploy?" --body "Migration tested in staging, need go/no-go."

A human (or a dashboard/cron job watching the queue) reviews open decisions and acks them once resolved:

crewmail decisions          # open (un-acked) decision requests
crewmail decisions --all    # include ones already acked
crewmail ack --agent HUMAN --id m-1234567890-ab12

MCP server setup

crewmail mcp runs a minimal Model Context Protocol server over stdio, exposing five tools (crewmail_inbox, crewmail_send, crewmail_ack, crewmail_status, crewmail_escalate) so an agent can use crewmail natively instead of shelling out.

Add it to your MCP client config (e.g. .mcp.json, or Claude Desktop's claude_desktop_config.json):

{
  "mcpServers": {
    "crewmail": {
      "command": "npx",
      "args": ["crewmail", "mcp", "--agent", "CLAUDE-01"]
    }
  }
}

--agent fixes the identity of the calling agent, so agent/from become optional in tool calls. Omit it to require an explicit agent/from argument on every call (useful if one server instance is shared by multiple identities).

Design principles

  1. Zero dependencies. Node.js built-ins only. npx crewmail works without installing anything else.
  2. No network. Local files only. Nothing leaves the machine.
  3. Append-only JSONL. The mail log is an audit trail; nothing is ever rewritten or deleted.
  4. Single-file CLI. bin/crewmail.mjs is the whole program — easy to read, easy to vendor into a repo directly.
  5. Agent-agnostic. Any runtime that can run a shell command (or speak MCP) can participate.
  6. Not an approval system. crewmail coordinates work between agents; it does not replace your code review or deployment approval workflow.

Commands

All commands accept --json (machine-readable output) and --dir <path> (explicit data directory, overriding auto-discovery).

Command Purpose
init [--commit-log] Create .crewmail/ in the current directory
register --code X [--name --runtime --model --role] Add or update an agent in the registry
send --from X --to A,B --kind K --subject S --body B [--thread --tag --priority] Append a message
inbox --agent X [--all] Unread (default) or all messages addressed to X, including ALL broadcasts
ack --agent X (--id M ... | --all) Write read receipts
log [--limit N --tag T --thread T] Recent messages, newest first
decisions [--all] Open (un-acked) decision_request messages to HUMAN; --all includes acked ones
heartbeat --agent X --status active|idle|blocked|done [--note] Update an agent's liveness status
status Table of agents: role, last heartbeat, unread count
watch [--agent X] [--interval <ms>] Poll and print new messages as they arrive (default 2000ms)
export Dump the full registry and message log as JSON
mcp [--agent X] Run the MCP server on stdio

Message kind: info | question | report | task | decision_request | ack. Reserved recipients: ALL (broadcast to every registered agent), HUMAN (the escalation queue). Subjects are capped at 80 characters. Exit codes: 0 success, 1 usage error, 2 data directory not found.

See docs/DESIGN.md for the full design spec.

Prior art & how crewmail differs

Agent-to-agent coordination is an active space; crewmail is one take on it, grown out of a private file bus the author has been running daily since 2026-07 to coordinate Claude Code and Codex CLI sessions building the same products. Related projects you should also consider:

  • agmsg — cross-vendor messaging for CLI coding agents over bash + SQLite, with real-time monitor delivery and tmux-based agent spawning. Great for interactive, session-orchestration workflows. crewmail was developed independently (different storage, language, and command surface) and focuses instead on a durable append-only audit log, typed message kinds, a built-in HUMAN decision queue, and an MCP server — coordination as a record, not session orchestration.
  • AgentMail — a hosted email API for AI agents (real email over the network). crewmail is unrelated: local files only, nothing leaves the machine.
  • CrewAI — an agent framework. crewmail is framework-agnostic and not affiliated; the name refers to your "crew" of coding agents.

License

MIT — see LICENSE.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选