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Get a researcher by their OpenAlex ID (e.g. A5023888391) or ORCID. Returns display_name, works_count, cited_by_count, summary_stats (h_index, i10_index), and last_known_institutions
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 |
|---|---|---|
| author_id | yes | OpenAlex author ID or ORCID |
{display_name, orcid, works_count, cited_by_count, last_known_institution}curl -X POST https://datafaucet.dev/api/sandbox \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_researcher","arguments":{"author_id":"A5023888391"}}}'import requests
response = requests.post(
"https://datafaucet.dev/api/sandbox",
json={
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "get_researcher",
"arguments": {
"author_id": "A5023888391"
}
}
}
)
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: "get_researcher",
arguments: {
"author_id": "A5023888391"
},
},
}),
});
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 get_researcher with zero integration code.
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