mcp-multi-tool-lab
Click on "Deploy 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., "@mcp-multi-tool-labsearch for flights from TPE to NRT on 2026-08-10"
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.
mcp-multi-tool-lab
一個輕量的多 provider MCP 測試資料/fixture:單一process掛載兩個 provider(eva_air 航空、uk_railway 鐵路),每個 provider 各暴露 5 個 MCP tool,資料全為記憶體內的假資料。設計目的是提供一個「MCP 後面有多個 tool」的可重複部署測試環境,方便驗證 MCP client 的 tool discovery、tool call 與多 provider 路由。
不含真實業務邏輯、資料庫或任何內部/機敏資料。
結構
agent.py # OpenAI Agents SDK 層:把兩個 provider 接成 Agent 的 mcp_servers
mcp_multi_tool_lab/
server.py # 用 Starlette 把兩個 provider 掛在 /<slug>/mcp 底下
providers/
eva_air.py # 航空 provider:5 個 tool + 記憶體假資料
uk_railway.py # 鐵路 provider:5 個 tool + 記憶體假資料Related MCP server: OpenAI-Compatible MCP Gateway
Provider 與 Tool 清單
Provider slug | MCP URL | Tools |
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安裝與啟動
poetry install
poetry run python -m mcp_multi_tool_lab.server伺服器預設監聽 http://localhost:8000。
連線方式
用 MCP client 連(建議)
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
async with streamablehttp_client("http://localhost:8000/eva_air/mcp") as (read, write, _):
async with ClientSession(read, write) as session:
await session.initialize()
tools = await session.list_tools()
print([t.name for t in tools.tools])用 curl 連(了解底層原理)
curl -N http://localhost:8000/eva_air/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"curl","version":"0"}}}'快速試用範例
eva_air_search_flights(origin="TPE", destination="NRT", date="2026-08-10")eva_air_create_provisional_booking(flight_id="BR001", passenger_name="Alice")eva_air_pay_booking(booking_id="EVA-0001")eva_air_dry_run_cancel(booking_id="EVA-0001")
uk_railway 系列 tool 用法相同,把 flight 換成 train 即可。
OpenAI Agents SDK 層
agent.py 用 openai-agents SDK 把兩個 provider 各接成一個 Agent:
Agent | MCP server | Tools |
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跑之前記得先啟動 mcp_multi_tool_lab.server(見上方「安裝與啟動」),agent.py 才能連得到這兩個 MCP server。
注意事項
所有資料都是進程內記憶體儲存,重啟伺服器即清空,不適合當持久化測試。
這是獨立、通用的測試資料專案,跟任何內部產品或公司內部 repo 沒有從屬關係。
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