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Integration

ScienceToStartup is an Agent Operating System for Research Commercialization

API and MCP Platform for Turning Research Papers into Buildable Product Signals.

OpenAI and ChatGPT are part of the main acquisition loop for the site. This page packages the endpoint, proof surfaces, llms files, and capability index into one install-and-test flow.

ChatGPT GuideMCP Endpointllms.txt
Use llms.txt and llms-full.txt to help models route into the right surfaces.
Use the MCP endpoint when you want tools and resources instead of raw HTTP-only docs.
Keep proof URLs in the loop so a human can validate the same object the model used.

Workflow

Query-led flow

  1. 1Start with llms.txt, capabilities.json, and the OpenAPI contract.
  2. 2Add the MCP endpoint for tool access when ChatGPT developer tooling supports the flow you need.
  3. 3Verify the same paper, topic, or benchmark page in the browser for human trust.
  4. 4Use keys and workspaces when you need authenticated execution.

Proof Surface Example

Canonical paper page

Stable evidence receipt, viability score, citations, and execution handoffs on one URL.

Open proof surface

curl

curl -X POST "https://sciencetostartup.com/api/mcp" \
  -H "Authorization: Bearer s2s_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "whoami",
      "arguments": {}
    }
  }'

Python

import requests

payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
        "name": "whoami",
        "arguments": {},
    },
}

response = requests.post(
    "https://sciencetostartup.com/api/mcp",
    headers={
        "Authorization": "Bearer s2s_YOUR_KEY",
        "Content-Type": "application/json",
    },
    json=payload,
    timeout=30,
)

TypeScript

const response = await fetch("https://sciencetostartup.com/api/mcp", {
  method: "POST",
  headers: {
    Authorization: "Bearer s2s_YOUR_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    jsonrpc: "2.0",
    id: 1,
    method: "tools/call",
    params: {
      name: "whoami",
      arguments: {},
    },
  }),
});

Canonical links

llms.txt

Short routing file for agents choosing between proof, developer, and install surfaces.

llms-full.txt

Exhaustive corpus and contract inventory for retrieval systems and agent builders.

MCP guide

Understand the hosted tool and resource contract.

See the live proof surface

Canonical Paper Page

Use the canonical paper page as a proof artifact.

Signal Canvas

Use Signal Canvas as the narrative proof surface.

Topic Page

Use this topic page as a durable research-area proof surface.

Benchmark Resource

Use the benchmark as a ranking and proof layer.

Dataset Resource

Use the public dataset as a machine-readable proof surface.

Stable contracts and discovery files

Developers

Hub for REST, MCP, integrations, and examples.

API Docs

OpenAPI, capabilities, and discovery documents.

REST API

HTTP integrations for research and workspace workflows.

MCP Server

Tool and resource contracts for agents and copilots.