ScienceToStartup
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Example

ScienceToStartup is an Agent Operating System for Research Commercialization

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

This example uses the weekly benchmark as the public shortlist layer, then hands selected papers into the same action chain that powers launch-pack generation and downstream execution.

Open BenchmarkExamples IndexCreate Key
Benchmark is the ranked shortlist layer.
Paper and Signal Canvas routes are the validation layer.
Build Loop or workspace actions are the execution layer.

Workflow

Query-led flow

  1. 1Pull the weekly benchmark snapshot or open the public scoreboard.
  2. 2Select top movers or high-signal papers for a shortlist.
  3. 3Open the paper or Signal Canvas surface for proof review.
  4. 4Create a workspace seed or trigger launch-pack generation.

Proof Surface Example

Benchmark scoreboard

Weekly ranking surface for high-signal papers and ranked commercialization comparisons.

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": "workspace_run_action",
      "arguments": {"workspace_id":"<workspace-id>","action":"launch_pack"}
    }
  }'

Python

import requests

payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
        "name": "workspace_run_action",
        "arguments": {"workspace_id":"<workspace-id>","action":"launch_pack"},
    },
}

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: "workspace_run_action",
      arguments: {"workspace_id":"<workspace-id>","action":"launch_pack"},
    },
  }),
});

Canonical links

Benchmark ranking API

Use the same ranked surface through REST.

Weekly benchmark roundup

See the recurring editorial wrapper for the same output.

Build Loop

Execution workspace that takes proof context into verify, export, and launch-pack actions.

See the live proof surface

Example paper page

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

Signal Canvas

Citation-first answer surface that turns paper context into research-to-product judgment.

Topic proof layer

Durable research-area page with paper counts, trend direction, authors, and top questions.

Benchmark scoreboard

Weekly ranking surface for high-signal papers and ranked commercialization comparisons.

Public dataset

Machine-readable export surface for papers, scores, tags, and canonical identifiers.

Build Loop

Execution workspace that takes proof context into verify, export, and launch-pack actions.

Stable contracts and discovery files

Official SDKs

JavaScript and Python client surfaces plus example quickstarts for REST, MCP, and workspace flows.

OpenAPI

Machine-readable REST contract for search, proof retrieval, Signal Canvas, and exports.

MCP endpoint

Remote MCP server for discovery tools, resources, and workspace actions.

Capability index

Product graph covering proof surfaces, install paths, and canonical action flows.

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.