The operating system for cs.AI commercialization.

curl

curl -X POST https://sciencetostartup.com/api/mcp \
  -H "Authorization: Bearer s2s_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"workspace_run_action","arguments":{"workspace_id":"YOUR_WORKSPACE_ID","run_kind":"workspace_operator","goal":"Assess whether this workspace is mature enough for build-room execution and draft the highest leverage next actions."}}}'

Python

from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

workspace_operator = Agent(
    name="Workspace Operator Client",
    model="gpt-5.4",
    mcp_servers=[
        MCPServerStreamableHttp(
            params={
                "url": "https://sciencetostartup.com/api/mcp",
                "headers": {"Authorization": "Bearer s2s_YOUR_KEY"},
            }
        )
    ],
    instructions="Call whoami first, then workspace_run_action with run_kind=workspace_operator and an explicit founder goal.",
)

result = Runner.run_sync(
    workspace_operator,
    "For workspace YOUR_WORKSPACE_ID, run workspace_operator and return the resulting summary plus proposal refs.",
)

TypeScript

import { Agent, run } from "@openai/agents";
import { MCPServerStreamableHttp } from "@openai/agents/mcp";

const mcpServer = new MCPServerStreamableHttp({
  url: "https://sciencetostartup.com/api/mcp",
  headers: { Authorization: "Bearer s2s_YOUR_KEY" },
});

const agent = new Agent({
  name: "Workspace Operator Client",
  model: "gpt-5.4",
  mcpServers: [mcpServer],
  instructions:
    "Call whoami first, then workspace_run_action with run_kind=workspace_operator and an explicit founder goal.",
});

const result = await run(
  agent,
  "Run workspace_operator for YOUR_WORKSPACE_ID and return the final summary, next actions, and proposal refs.",
);