VibeCode your first trading agent

Vibe Code an Agent Using MCP

1. Start with your editor open

○ In your Cursor project root (where .cursor/mcp.json lives), open a new file called trade_agent.py.

Sketch the skeleton import asyncio

import json

from mcp import ClientSession

from mcp.client.sse import sse_client

async def run_tool(server: str, tool_name: str, params: dict):

async with sse_client(url=server) as streams:

stdio, write = streams

session = ClientSession(stdio, write)

await session.initialize()

result = await session.call_tool(tool_name, params)

return result.content

async def main():

mcp_server = "https://mcp-jenius.rndm.io/sse"

# Example: crypto vs stock

btc_analysis = await run_tool(mcp_server, "web3_insights_analysis", {"crypto_symbol": "BTC"})

aapl_signal = await run_tool(mcp_server, "web2_insights_analysis", {"asset_symbol": "AAPL"})

print("BTC Analysis:", json.dumps(btc_analysis, indent=2))

print("AAPL Signal:", json.dumps(aapl_signal, indent=2))

if __name__ == "__main__":

asyncio.run(main())

Run it for the first time You should see pretty-printed JSON for your BTC and AAPL analyses.

Next-level enhancements

1. Push signals into a dashboard or messaging app (Slack, Telegram).

2. Store outputs in a database or as timestamped JSON files.

3. Chain tools for composite strategies (e.g., on a strong crypto signal, automatically fetch related on-chain metrics).

With this “vibe code” blueprint, you can spin up an MCP-powered trading agent in minutes—then layer on the features that best fit your workflow. Enjoy!