orchestrator-mcp
Allows using OpenAI models (e.g., GPT-4o-mini, GPT-5) for various stages in multi-model agent orchestration, including planning, coding, reviewing, and delivering tasks.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@orchestrator-mcprun daily-dev pipeline to implement new API endpoint"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
orchestrator-mcp
多模型 Agent 编排 MCP:plan → code → review → deliver。
Handoff schema 固定(
schemas/)Provider 按厂商(deepseek / moonshot / zhipu / openai),model 按 stage 配置
别名:
glm→ zhipu,gpt→ openai凭证:环境变量 → WebUI 本地 JSON →
~/Desktop/服务器.mdWeb 配置界面:编辑 Provider Key / Base URL / 默认模型,以及各 Profile 的 Stage 模型
快速开始
cd orchestrator-mcp
./verify.sh # 离线 stub 自测(含 WebUI API 冒烟)
./start.sh # MCP :18067
./start-webui.sh # 配置 WebUI :18068 → http://127.0.0.1:18068
# 可选:只测 plan 阶段真实 DeepSeek 调用
ORCHESTRATOR_LIVE_TEST=1 ./verify.shRelated MCP server: ForgeSwarm
Web 配置界面
功能 | 说明 |
Providers | 编辑 |
Stages | 按 Profile 覆盖 plan/code/review/deliver 的 provider + model;写入 |
本地配置文件不进 git。环境变量仍优先于 WebUI 写入的值。
Profile
Profile | 用途 |
| 离线自测,不调 API |
| deepseek plan / glm code / gpt review / moonshot deliver |
| 示例:plan 换 kimi |
同一 OpenAI 账号下 plan 用 gpt-4o-mini、code 用 gpt-5:只改 YAML 里各 stage 的 model,不用建两个 provider。
stages:
plan:
provider: gpt
model: gpt-4o-mini
code:
provider: gpt
model: gpt-5凭证环境变量
Provider | Env | 默认 Base URL |
deepseek |
| |
moonshot |
| |
zhipu/glm |
| |
openai/gpt |
| https://api.openai.com/v1 · |
codex-lb/codex |
| https://codex-lb.vvicat.dev/backend-api/codex · |
Codex 中转(Responses API)
与 Codex CLI 配置对应关系:
model = "gpt-5.4"
model_reasoning_effort = "medium"
model_provider = "codex-lb"
env_key = "CODEX_LB_API_KEY"
[model_providers.codex-lb]
base_url = "https://codex-lb.vvicat.dev/backend-api/codex"
wire_api = "responses"在 WebUI Providers → Codex 中转 填写:
字段 | 值 |
API 密钥 | 同 |
Base URL |
|
默认模型 |
|
Wire API |
|
Reasoning Effort |
|
Stage 里把 review/deliver 的 provider 选 codex-lb(或别名 codex),model 填 gpt-5.4。
注意:/chat/completions 在该中转上返回 405;必须用 Responses 协议。
可选覆盖:CODEX_LB_BASE_URL、DEEPSEEK_BASE_URL、MOONSHOT_BASE_URL、ZHIPU_BASE_URL、OPENAI_BASE_URL
服务器.md 标签(下一行或同行):deepseekApiKey、moonshotApiKey、zhipuApiKey、openaiApiKey
MCP 工具
工具 | 说明 |
| 各 provider 是否已配置 key |
| 检查单个 provider |
| 编排执行 |
| 运行时换 provider/model |
Cursor 配置
本仓库已在 .cursor/mcp.json 写好配置(stdio 模式,不用手动 ./start.sh)。
用 Cursor 打开
localopenclaw仓库根目录Settings → Tools & MCP,确认 orchestrator-mcp 已启用(绿点)
若没有,点 Refresh 或重启 Cursor
若仍看不到:Settings → MCP → Edit Config,确认项目级 .cursor/mcp.json 已加载。
方式 A(推荐,已写入项目):Cursor 自动拉起进程
{
"mcpServers": {
"orchestrator-mcp": {
"command": ".../orchestrator-mcp/.venv/bin/python",
"args": ["-m", "orchestrator_mcp"],
"env": {
"PYTHONPATH": ".../orchestrator-mcp/src",
"ORCHESTRATOR_MCP_TRANSPORT": "stdio"
}
}
}
}方式 B:先 ./start.sh,再用 URL(需保持终端进程运行)
{
"mcpServers": {
"orchestrator-mcp": {
"url": "http://127.0.0.1:18067/mcp"
}
}
}This server cannot be installed
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