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Search research fields and topics by name. Returns results[] with id, display_name, level, description, works_count, and cited_by_count for each concept
OpenAlex: Keyless scholarly search: papers, researchers, institutions, and research concepts
Search 250M+ scholarly papers, researchers, institutions, and research concepts.
Unlimited calls, no rate limits, custom domain.
claude mcp add datafaucet-sandbox https://datafaucet.dev/api/sandboxNew here? Start with these zero-config tools:
| Name | Required | Description |
|---|---|---|
| query | yes | Research field or topic name |
{results: [{id, display_name, level, description, works_count}]}curl -X POST https://datafaucet.dev/api/sandbox \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search_concepts","arguments":{"query":"machine learning"}}}'import requests
response = requests.post(
"https://datafaucet.dev/api/sandbox",
json={
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "search_concepts",
"arguments": {
"query": "machine learning"
}
}
}
)
print(response.json())const response = await fetch("https://datafaucet.dev/api/sandbox", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
jsonrpc: "2.0",
id: 1,
method: "tools/call",
params: {
name: "search_concepts",
arguments: {
"query": "machine learning"
},
},
}),
});
const data = await response.json();
console.log(data.result.content[0].text);claude mcp add datafaucet-sandbox https://datafaucet.dev/api/sandbox
All 230 sandbox tools become available instantly. No API keys needed.
Why use MCP instead of calling the API directly?
Raw API
Auth, parsing, error handling, retries, types. ~2 hours per endpoint.
Via MCP
One config line. AI agent calls search_concepts with zero integration code.
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