Material takeoffs and job bids for contractors: concrete, paint, framing, roofing. Connect ChatGPT and OpenAI Agents to the WingMan MCP gateway once and these tools are available in every conversation.
With the OpenAI Agents SDK (Python), connect over Streamable HTTP as below. The same URL works as a remote MCP tool in the Responses API and as a custom connector in ChatGPT developer mode.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
async with MCPServerStreamableHttp(name="wingman", params={"url": "https://wingmanprotocol.com/mcp", "headers": {"X-Wingman-Tools": "full"}}) as wingman:
agent = Agent(name="Assistant", mcp_servers=[wingman])
result = await Runner.run(agent, "Use the wingman tools for this task.")
print(result.final_output)
asyncio.run(main())
# Responses API instead of the SDK:
# tools=[{"type": "mcp", "server_label": "wingman", "server_url": "https://wingmanprotocol.com/mcp", "require_approval": "never"}]Names and descriptions come straight from the live tool registry.
concreteCubic yards, 60/80-lb bag counts and ready-mix cost for slabs, columns or tubes.paintGallons of paint and number of coats for a room from wall dimensions, openings and coverage.framingStud, plate and header counts plus board-feet and cost for a framed wall.bid_estimatorBuild a client job bid from cost components: labor hours x rate + materials + equipment + subs, then overhead, contingency and margin into an…roof_cost_estimatorBallpark roof replacement cost from squares/sqft, material, pitch, tear-off, and stories.These tools sit outside the default tool list, so the config above sets X-Wingman-Tools: full to load the whole catalogue. Without it, your agent can still reach them with discover_tools, then get_tool_schema, then tools/call.
Give ChatGPT and OpenAI Agents a task that needs it, for example “use concrete from wingman”. The tool call goes to https://wingmanprotocol.com/mcp and the result comes back into the conversation.
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