๐ŸŽ“ Research MCP โ€” AI Paper Search & Citations avatar

๐ŸŽ“ Research MCP โ€” AI Paper Search & Citations

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๐ŸŽ“ Research MCP โ€” AI Paper Search & Citations

๐ŸŽ“ Research MCP โ€” AI Paper Search & Citations

๐ŸŽ“ Academic research, scholarly papers, arXiv, PubMed, Google Scholar MCP server for AI agents (Claude Desktop, Cursor, OpenAI Agents SDK). Search papers + citations + authors + abstracts via MCP โ€” built for literature-review and research AI workflows. Free tier available.

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Stephan Corbeil

Stephan Corbeil

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๐ŸŽ“ Academic Research MCP Server โ€” arXiv, Google Scholar & OpenAlex for Claude / ChatGPT

Connect AI agents to live academic-research data through the Model Context Protocol โ€” arXiv papers, Google Scholar citations, OpenAlex metadata, and research-trend signal. A drop-in alternative to the rate-limited Semantic Scholar API, Connected Papers, Scite, and direct OpenAlex queries.

Why This MCP Server Beats Semantic Scholar API, Connected Papers, OpenAlex & Scite

FeatureNexGenData Academic Research MCPSemantic Scholar APIConnected Papers APIOpenAlex directScite
CostPay-per-event, ~$0.003 per tool callFree, heavy rate-limitFree UI, paid APIFree, query-cap$20-50 / user / month
AI agent integrationNative MCP โ€” Claude Desktop, CursorNone โ€” REST onlyNone โ€” UI onlyNoneNone
Rate limitApify-managed100 req / 5 minStrict100,000 / day capPer-seat
CoveragearXiv + Scholar + OpenAlex + NIHOpen papers onlyVisual graphOpen papersCitation context
Time-to-first-call< 60 secondsAPI-key signupAccount + planAPI keyPer-seat license
AuthApify tokenAPI key + tierPlan + API keyEmail + keyInstitution / seat
OutputStructured JSON for LLM function-callsJSONVisual graphJSONJSON

Most research teams pick this MCP server because it is the only way to give an AI agent unified access to four academic-data sources at once โ€” without juggling separate rate-limited keys.

What You Get

Tools exposed to your AI agent:

  • search_papers โ€” keyword / author / field search across arXiv + Scholar + OpenAlex
  • get_paper_details โ€” abstract, authors, year, citation count, references, DOI
  • find_related_papers โ€” co-citation + bibliographic-coupling graph traversal
  • get_author_profile โ€” h-index, total citations, paper list, affiliation history
  • citation_trends โ€” citations-per-year curve for a paper or author
  • get_grant_data โ€” NIH RePORTER grant lookup by PI, institution, project number
  • subject_trends โ€” paper-volume growth per field / keyword over time

Each response is clean JSON tuned for LLM tool-use โ€” no PDF parsing, no XML feed pagination.

Use Cases

  • AI research assistants โ€” Claude pulls top 20 papers on a topic, ranks by recency + citation count, summarizes
  • Lit-review copilots โ€” multi-step agents draft a literature review by chaining search_papers โ†’ find_related_papers โ†’ get_paper_details
  • Grant-discovery agents โ€” match a research lab's recent papers to NIH RePORTER grant calls
  • Competitive research intel โ€” track papers from a competitor's R&D group over time
  • Academic publishers โ€” automate "papers citing this paper" alerts via scheduled MCP calls
  • VC due-diligence โ€” find lead inventors behind a deep-tech startup before a meeting
  • Policy think-tanks โ€” surface citation-network influence of competing research camps

Quick Start

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/academic-research-mcp-server").call(run_input={
"tool": "search_papers",
"params": {"query": "retrieval augmented generation", "year_min": 2024, "limit": 25}
})
for paper in client.dataset(run["defaultDatasetId"]).iterate_items():
print(paper["title"], paper["citations"])

Or connect Claude Desktop / Cursor / Cline directly to the MCP endpoint and ask in natural language: "Find me the top 10 most-cited 2025 papers on diffusion models and summarize the methodology differences."

Pricing

Pay-per-event โ€” you only pay for tool calls that return data:

  • Actor Start: ~$0.0002
  • Tool call: $0.003 per call

A typical lit-review agent issues 30-80 tool calls per task โ†’ $0.10-$0.25 total.

Use caseActor
Google Scholar bulk paper + citation scraperGoogle Scholar Scraper
arXiv keyword search + bulk paper exportarXiv Scraper
NIH RePORTER grant + funding lookupNIH RePORTER Grants Scraper
News + press release monitoring for AI agentsNews MCP Server
Finance + market data for AI agentsFinance MCP Server
Developer ecosystem data for AI agentsDeveloper Tools MCP Server
Wikipedia structured-knowledge scraperWikipedia Scraper
IRS 990 nonprofit financial filingsIRS 990 Nonprofit Explorer

FAQ

Q: How does this compare to Semantic Scholar's API? Semantic Scholar's free API caps at 100 req / 5 minutes and rejects bulk pulls. This MCP server multiplexes across four sources with Apify-managed rate limits so an agent can run a 50-call lit-review uninterrupted.

Q: Can the agent call this from Claude Desktop? Yes โ€” point Claude Desktop's MCP config at the Apify endpoint URL for this actor. Tool discovery is automatic.

Q: Are paywalled papers included? Metadata only โ€” title, abstract, authors, citations. Full-text PDFs require institutional access through the publisher.

Q: How fresh is the data? arXiv is refreshed daily, Scholar and OpenAlex hourly, NIH RePORTER weekly.

Q: What about citation graphs? Use find_related_papers โ€” returns co-citation neighbors plus bibliographic-coupling matches.

Q: Can I get DOIs for cross-referencing? Yes โ€” every paper response includes DOI where one exists.

Q: Is this safe for production research products? Yes โ€” runs on Apify auto-scaling infrastructure with logging + retry semantics built in.

About NexGenData

NexGenData publishes 260+ buyer-intent actors plus a family of MCP servers for AI agent workflows (finance, news, sports, real-estate, developer tools, academic research, premium data). All pay-per-result. Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b


How NexGenData Pricing Works

Every NexGenData actor uses pay-per-event pricing โ€” you only pay for results that actually land in your dataset. No monthly minimum, no seat fees, no surprise overage bills.

  • Actor Start: a single-event charge each time you spin the actor up (scaled to memory size)
  • Result: charged per item written to the default dataset
  • No charge for retries, internal proxy rotation, or failed sub-requests โ€” those are absorbed by the platform

If you only need the data once a quarter, you only pay once a quarter. If you scale to millions of records, the unit cost stays the same.

Apify Platform Bonus

New to Apify? Sign up with the NexGenData referral link โ€” you get free platform credits on signup (enough for several thousand free results) and you help fund the maintenance of this actor fleet.

Integration Surface

Every actor in the NexGenData catalog can be triggered from:

  • Apify console โ€” point-and-click run
  • Apify API โ€” REST + webhooks
  • Apify Python / JS SDKs โ€” programmatic batch
  • Zapier, Make.com, n8n โ€” official integrations
  • MCP โ€” many actors are exposed as MCP tools for Claude / ChatGPT / Cursor agents
  • Schedules โ€” built-in cron for daily / weekly / monthly runs
  • Webhooks โ€” POST results to any HTTPS endpoint on dataset write

Support

NexGenData maintains 260+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get a response within 24 hours. Roadmap requests are welcome โ€” high-demand features ship in the next version.

๐Ÿ  Home: thenextgennexus.com ๐Ÿ“ฆ Full catalog: apify.com/nexgendata