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Scholar Feed MCP Server

Enables searching and analyzing over 560,000 CS/AI/ML research papers with LLM-powered novelty scoring and summaries. Supports literature reviews, trend monitoring, benchmark tracking, and deep research sessions through 23 specialized tools.

glama
Updated
Apr 14, 2026

Scholar Feed MCP Server

Search 560,000+ CS/AI/ML research papers with LLM-powered novelty analysis from Claude Code, Cursor, or any MCP client.

Scholar Feed indexes arXiv papers daily and ranks them using a multi-signal scoring system (recency, citation velocity, institutional reputation, code availability). Each paper has an LLM-generated summary and novelty score.

Quick Start

npx scholar-feed-mcp init

This interactive wizard will:

  1. Optionally ask for an API key (or skip for anonymous access)
  2. Detect your MCP client (Claude Code, Cursor, or Claude Desktop)
  3. Write the config and verify the connection

No API key required. Anonymous access gives you 100 calls/day — enough for a typical research session. For higher limits (500/day), get a free key at scholarfeed.org/settings.

Try asking: "Search for recent papers on test-time compute scaling"

What You Can Do

Technology scouting — "What novel research on retrieval-augmented generation was published this month?"

Literature review — "Find papers similar to 2401.04088 and export their BibTeX"

Trend monitoring — "What's trending in cs.CV this week? Summarize the top 3."

Deep dives — "Run a deep research session on 'reasoning in large language models'"

Benchmark tracking — "Show me the MMLU leaderboard and compare GPT-4 vs LLaMA-3"

Author discovery — "Who are the top researchers working on efficient LLM inference?"

Manual Installation

Claude Code

# Without API key (anonymous, 100 calls/day)
claude mcp add scholar-feed -- npx -y scholar-feed-mcp

# With API key (500 calls/day)
claude mcp add scholar-feed -e SF_API_KEY=sf_your_key_here -- npx -y scholar-feed-mcp

Cursor (.cursor/mcp.json)

{
  "mcpServers": {
    "scholar-feed": {
      "command": "npx",
      "args": ["-y", "scholar-feed-mcp"]
    }
  }
}

To add an API key, add "env": { "SF_API_KEY": "sf_your_key_here" } to the config.

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "scholar-feed": {
      "command": "npx",
      "args": ["-y", "scholar-feed-mcp"]
    }
  }
}

Project-scoped (.mcp.json)

{
  "mcpServers": {
    "scholar-feed": {
      "command": "npx",
      "args": ["-y", "scholar-feed-mcp"],
      "env": { "SF_API_KEY": "${SF_API_KEY}" }
    }
  }
}

Windows note: Use "command": "cmd" and "args": ["/c", "npx", "-y", "scholar-feed-mcp"].

Available Tools (23)

Core Search & Discovery

ToolDescriptionKey Parameters
search_papersFull-text keyword search with filtersq, category, novelty_min, days, method_category, task, dataset, contribution_type, task_category, has_results, cursor, limit
get_paperGet full paper details by arXiv IDarxiv_id, fields
find_similarFind similar papers via embedding + bibliographic couplingarxiv_id, limit, days
get_citationsCitation graph (outgoing refs or incoming citations)arxiv_id, direction, limit, fields
whats_trendingToday's trending papers by composite scorecategory, limit, fields, exclude_ids
batch_lookupLook up multiple papers at oncearxiv_ids (max 50), fields

Paper Content

ToolDescriptionKey Parameters
fetch_fulltextExtract results/experiments from LaTeX sourcearxiv_id
fetch_repoGet GitHub repo README + file treearxiv_id
export_bibtexExport BibTeX for papersarxiv_ids (max 50)
get_paper_resultsStructured benchmark results from a paperarxiv_id

Benchmarks & Methods

ToolDescriptionKey Parameters
search_benchmarksFind datasets/benchmarks by nameq, limit
get_leaderboardSOTA leaderboard for a datasetdataset, metric, limit
get_benchmark_statsScore distribution stats (min, max, median, etc.)dataset, metric
get_benchmark_timelineRaw score data points over timedataset, metric
search_by_methodSearch by technique name (LoRA, YOLO, DPO, etc.)q, contribution_type, task_category, limit
compare_methodsSide-by-side model comparison across benchmarksmodels (2-10), dataset, metric

Authors

ToolDescriptionKey Parameters
discover_authorsFind researchers by topic or nameq, field, limit
get_authorDetailed author profile (h-index, topics, top papers)author_id
get_author_papersAll papers by an author (paginated)author_id, limit, page

Research

ToolDescriptionKey Parameters
get_research_landscapeAggregated landscape stats for a topicq, limit
deep_researchMulti-round research synthesis (30-120s)topic, depth
refine_researchFollow-up question on a completed research reportreport_id, question, date_from, date_to

Utility

ToolDescriptionKey Parameters
check_connectionVerify API key, show plan and usage

Novelty Score

Every paper has an llm_novelty_score from 0.0 to 1.0:

RangeMeaningExample
0.7+Paradigm shift or broad SOTANew architecture that changes the field
0.5-0.7Novel method with strong resultsNew training technique with clear gains
0.3-0.5Incremental improvementApplying known method to new domain
<0.3Survey, dataset, or minor extensionLiterature review, benchmark release

Use novelty_min: 0.5 in search_papers to filter for genuinely novel work.

Rate Limits

EndpointLimit
check_connection60/min
search_papers30/min
get_paper60/min
find_similar20/min
get_citations30/min
whats_trending30/min
fetch_fulltext10/min
batch_lookup20/min
fetch_repo10/min
export_bibtex20/min
deep_research5/min
refine_research5/min
search_benchmarks30/min
get_leaderboard30/min
get_benchmark_stats30/min
get_benchmark_timeline30/min
search_by_method30/min
compare_methods20/min
discover_authors20/min
get_author60/min
get_author_papers30/min
get_research_landscape10/min
get_paper_results30/min

Responses include X-RateLimit-Limit, X-RateLimit-Remaining, and X-RateLimit-Reset headers.

Example Response

search_papers with q: "attention mechanism" returns:

{
  "papers": [
    {
      "arxiv_id": "2401.04088",
      "title": "Attention Is All You Need (But Not All You Get)",
      "authors": ["A. Researcher", "B. Scientist"],
      "year": 2024,
      "categories": ["cs.LG", "cs.AI"],
      "primary_category": "cs.LG",
      "arxiv_url": "https://arxiv.org/abs/2401.04088",
      "has_code": true,
      "github_url": "https://github.com/example/repo",
      "citation_count": 42,
      "rank_score": 0.73,
      "llm_summary": "Proposes a sparse attention variant that reduces compute by 60% while matching dense attention accuracy on 5 benchmarks.",
      "llm_novelty_score": 0.55
    }
  ],
  "total": 1847,
  "page": 1,
  "limit": 20,
  "next_cursor": "eyJzIjogMC43MywgImlkIjogIjI0MDEuMDQwODgifQ=="
}

Pass next_cursor back to get the next page (keyset pagination — more stable than page numbers for large result sets).

Verify Installation

After setup, ask your AI assistant to run check_connection. You should see:

{
  "status": "ok",
  "plan": "free",
  "key_name": "my-key",
  "usage_today": 0
}

Environment Variables

VariableRequiredDefaultDescription
SF_API_KEYNoYour Scholar Feed API key (starts with sf_). Without it, runs in anonymous mode (100 calls/day).
SF_API_BASE_URLNoProduction URLOverride API base URL

Development

npm install
npm run build      # Build to build/
npm run dev        # Watch mode
npm run typecheck  # Type check without emitting
npm test           # Run tests

Contributing

See CONTRIBUTING.md for guidelines.

Troubleshooting

"Authentication failed: your SF_API_KEY is invalid" The key may have been revoked. Generate a new one at scholarfeed.org/settings. Or remove the key to use anonymous mode.

"Rate limit exceeded" or "Anonymous daily limit exceeded" Anonymous mode allows 100 calls/day. Get a free API key at scholarfeed.org/settings for 500 calls/day.

Tool calls time out or fail silently Ensure Node.js 18+ is installed (node --version). Older versions lack the native fetch API.

Stale npx cache If you're stuck on an old version after an update: npx --yes scholar-feed-mcp@latest

Windows: "command not found" Use "command": "cmd" with "args": ["/c", "npx", "-y", "scholar-feed-mcp"] in your MCP config.

License

MIT

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