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LION Research Agent
x402
LION Research Agent is a paid API for AI agents from lion-research-agent.lionmaster-operations.workers.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-14).
Performs deep research on a given topic and returns structured insights including a summary, key findings, cited sources, and a confidence score.
Price / call$0.001
Success—
StatusUnknown
How this service works
Deep research agent that returns structured insights with summary, key findings, sources and confidence.
Output
Returns a JSON object with a prose summary of the topic, an array of key findings, an array of source URLs or references, a confidence score (0-1) reflecting result reliability, and a last_updated timestamp.
Example use cases
Example prompt
“Can you do a deep research on the current state of quantum computing hardware and give me a structured breakdown with key findings, sources, and how confident you are in the results?”
Technical details
Endpoint
POSThttps://lion-research-agent.lionmaster-operations.workers.dev/researchWhen to prefer
Choose this endpoint when you need structured, citation-backed research output with an explicit confidence rating — particularly useful for agent pipelines that need to reason about result reliability or pass findings downstream in a structured format rather than raw web search results.
Side effects
- Missing required 'query' field returns a 400 or validation error
- Vague or ambiguous query may produce low confidence score
- External sources unavailable may reduce source count and lower confidence
- Payment not provided or insufficient USDC may result in 402 payment required error
- Network timeout if underlying research process takes too long
Input
{
"query": "artificial intelligence applications in healthcare"
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| queryrequired | string | The research topic or question |
Output
{
"result": {
"sources": [],
"summary": "```\n{\n \"summary\": \"Artificial intelligence (AI) has numerous applications in healthcare, including diagnosis, treatment, patient engagement, and personalized medicine. AI can analyze large amounts of medical data, identify patterns, and provide insights to improve patient outcomes. AI-powered systems can also help with clinical decision support, medical imaging, and predictive analytics.\",\n \"key_findings\": [\n \"AI can improve diagnosis accuracy and speed\",\n \"AI-powered chatbots can enhance patient engagement and support\",\n \"AI can help with personalized medicine and targeted treatments\",\n \"AI can analyze medical images and detect abnormalities\",\n \"AI can predict patient outcomes and identify high-risk patients\"\n ],\n \"sources\": [\n {\n \"title\": \"Artificial Intelligence in Healthcare\",\n \"url\": \"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7142495/\"\n },\n {\n \"title\": \"AI in Healthcare: Past, Present, and Future\",\n \"url\": \"https://www.sciencedirect.com/science/article/pii/S1532046420300456\"\n },\n {\n \"title\": \"The Role of Artificial Intelligence in Healthcare\",\n \"url\": \"https://healthitanalytics.com/news/the-role-of-art",
"key_findings": []
},
"payment": {
"txHash": "0xf986ece7782136a63ba69aa34eb63e6d16181a171f4f4748726e92f5ddfb9417",
"settled": true
}
}Schema · Response
| Field | Type | Description |
|---|---|---|
| sources | array | |
| summary | string | |
| confidence | number | |
| key_findings | array | |
| last_updated | string |
Tags
x402
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