Which integrations are available for this server?

Provides tools for searching and analyzing arXiv research papers, including full-text search, paper details retrieval, citation analysis, and trending paper discovery with LLM-powered novelty scoring. Enables access to GitHub repositories associated with research papers, including fetching repository READMEs and file trees for code availability analysis. Provides tools for extracting content from LaTeX source files of research papers, including results and experiments sections for detailed analysis.

How do I use Scholar Feed MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Scholar Feed MCP Server find recent papers on efficient LLM inference with high novelty scores" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

de en es ja ko ru zh

Scholar Feed MCP Server

by YGao2005

Overview Schema Related Servers Score Discussions

TypeScript

Remote

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:

Ask for your API key (get one at scholarfeed.org/settings)
Detect your MCP client (Claude Code, Cursor, or Claude Desktop)
Write the config and verify the connection

That's it. 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

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"],
      "env": { "SF_API_KEY": "sf_your_key_here" }
    }
  }
}

Claude Desktop (claude_desktop_config.json)

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

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

Tool	Description	Key Parameters
`search_papers`	Full-text keyword search with filters	`q`, `category`, `novelty_min`, `days`, `method_category`, `task`, `dataset`, `contribution_type`, `task_category`, `has_results`, `cursor`, `limit`
`get_paper`	Get full paper details by arXiv ID	`arxiv_id`, `fields`
`find_similar`	Find similar papers via embedding + bibliographic coupling	`arxiv_id`, `limit`, `days`
`get_citations`	Citation graph (outgoing refs or incoming citations)	`arxiv_id`, `direction`, `limit`, `fields`
`whats_trending`	Today's trending papers by composite score	`category`, `limit`, `fields`, `exclude_ids`
`batch_lookup`	Look up multiple papers at once	`arxiv_ids` (max 50), `fields`

Paper Content

Tool	Description	Key Parameters
`fetch_fulltext`	Extract results/experiments from LaTeX source	`arxiv_id`
`fetch_repo`	Get GitHub repo README + file tree	`arxiv_id`
`export_bibtex`	Export BibTeX for papers	`arxiv_ids` (max 50)
`get_paper_results`	Structured benchmark results from a paper	`arxiv_id`

Benchmarks & Methods

Tool	Description	Key Parameters
`search_benchmarks`	Find datasets/benchmarks by name	`q`, `limit`
`get_leaderboard`	SOTA leaderboard for a dataset	`dataset`, `metric`, `limit`
`get_benchmark_stats`	Score distribution stats (min, max, median, etc.)	`dataset`, `metric`
`get_benchmark_timeline`	Raw score data points over time	`dataset`, `metric`
`search_by_method`	Search by technique name (LoRA, YOLO, DPO, etc.)	`q`, `contribution_type`, `task_category`, `limit`
`compare_methods`	Side-by-side model comparison across benchmarks	`models` (2-10), `dataset`, `metric`

Authors

Tool	Description	Key Parameters
`discover_authors`	Find researchers by topic or name	`q`, `field`, `limit`
`get_author`	Detailed author profile (h-index, topics, top papers)	`author_id`
`get_author_papers`	All papers by an author (paginated)	`author_id`, `limit`, `page`

Research

Tool	Description	Key Parameters
`get_research_landscape`	Aggregated landscape stats for a topic	`q`, `limit`
`deep_research`	Multi-round research synthesis (30-120s)	`topic`, `depth`
`refine_research`	Follow-up question on a completed research report	`report_id`, `question`, `date_from`, `date_to`

Utility

Tool	Description	Key Parameters
`check_connection`	Verify API key, show plan and usage	—

Novelty Score

Every paper has an llm_novelty_score from 0.0 to 1.0:

Range	Meaning	Example
0.7+	Paradigm shift or broad SOTA	New architecture that changes the field
0.5-0.7	Novel method with strong results	New training technique with clear gains
0.3-0.5	Incremental improvement	Applying known method to new domain
<0.3	Survey, dataset, or minor extension	Literature review, benchmark release

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

Rate Limits

Endpoint	Limit
`check_connection`	60/min
`search_papers`	30/min
`get_paper`	60/min
`find_similar`	20/min
`get_citations`	30/min
`whats_trending`	30/min
`fetch_fulltext`	10/min
`batch_lookup`	20/min
`fetch_repo`	10/min
`export_bibtex`	20/min
`deep_research`	5/min
`refine_research`	5/min
`search_benchmarks`	30/min
`get_leaderboard`	30/min
`get_benchmark_stats`	30/min
`get_benchmark_timeline`	30/min
`search_by_method`	30/min
`compare_methods`	20/min
`discover_authors`	20/min
`get_author`	60/min
`get_author_papers`	30/min
`get_research_landscape`	10/min
`get_paper_results`	30/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

Variable	Required	Default	Description
`SF_API_KEY`	Yes	—	Your Scholar Feed API key (starts with `sf_`)
`SF_API_BASE_URL`	No	Production URL	Override 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

"SF_API_KEY environment variable is required" Your MCP client isn't passing the env var. Double-check the env block in your config matches the examples above.

"Authentication failed: your SF_API_KEY is invalid" The key may have been revoked. Generate a new one at scholarfeed.org/settings.

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

Install Server

security – no known vulnerabilities

license - permissive license

quality - A tier

How are these scores calculated?

Resources

Need Help?

Related Servers

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Tools

View all tools

Latest Blog Posts

Tool Definition Quality Score (TDQS)
By punkpeye on April 3, 2026.
mcp
The Hackers Who Tracked My Sleep Cycle
By punkpeye on March 26, 2026.
security
Open Source Has a Bot Problem
By punkpeye on March 19, 2026.
open source

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/YGao2005/scholar-feed-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server