Scholar Feed MCP Server
The Scholar Feed MCP Server enables search and analysis of 560,000+ CS/AI/ML research papers with LLM-powered summaries, novelty scoring, and deep research synthesis.
Search & Discovery — Full-text or semantic search with filters for category, novelty, recency, method, task, dataset, and contribution type; trending papers ranked by recency, citation velocity, and institutional reputation; batch lookup of up to 50 papers at once.
Paper Details & Content — Retrieve metadata, LLM-generated summaries, novelty scores, and structured extraction (methods, tasks, baselines); extract results/experiments from LaTeX source; fetch GitHub repo READMEs and file trees; export BibTeX for up to 50 papers.
Citation & Similarity — Explore citation graphs (incoming/outgoing) and discover related papers via embedding similarity and bibliographic coupling.
Benchmarks & Methods — Search 20k+ benchmarks, view SOTA leaderboards, analyze score distributions and timelines, search by method name (e.g., LoRA, DPO), compare 2–10 models side-by-side, and extract structured quantitative results from specific papers.
Authors — Discover researchers by topic or name; view detailed profiles (h-index, citations, global rank, top papers); retrieve paginated paper lists by author.
Research Synthesis — Run deep research sessions (60–300s) producing structured reports with clusters, gap analysis, and evidence chains; refine reports with follow-up questions.
Landscape Analysis — Aggregated topic stats: methods used, benchmarks evaluated, active authors, publication velocity, and novelty distribution.
Utility — Verify API connection, subscription plan, and daily usage limits.
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.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Scholar Feed MCP Serverfind 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.
Scholar Feed MCP Server
Search 600,000+ 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 initThis interactive wizard will:
Optionally ask for an API key (or skip for anonymous access)
Detect your MCP client (Claude Code, Cursor, or Claude Desktop)
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 (1,000/day per account), get a free key at scholarfeed.org/settings.
Try asking: "Search for recent papers on test-time compute scaling"
Migrating from v1.x to v3.0.0
v3.0.0 is a hard cutover — there is no deprecation window. The previous v1.x tool surface was consolidated down to 8 focused tools. Existing agents using removed tools will need to update their calls before upgrading.
Breaking changes — full replacement table
Removed tool (v1.x) | v3 replacement |
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| Removed — errors signal connectivity. No action needed; remove any health-check calls. |
| Removed — 0 observed calls in production. Backend route preserved for skill use. |
The 8 v3 tools
Tool | Description |
| Semantic + keyword search. Now also handles similar-paper discovery ( |
| Full paper details by arXiv ID. Now also handles batch lookup ( |
| Citation graph — outgoing refs or incoming citations ( |
| Extract results/experiments sections from LaTeX source. |
| Find authors by name/topic query ( |
| Co-authorship neighborhood for an author — edges derived live from the citation graph. |
| Get a 768-dim Gemini embedding for a text string (useful for HyDE and custom similarity). |
| Cheap retrieval orientation for a research area — top papers, subfields, open problems. No Pro quota. |
New in v3.0.0 (reaching npm for the first time):
find_author— mergeddiscover_authors+get_authorinto a single tool with exactly-one-of (qorid) semantics.get_field_orientation— the cheap-retrieval half of the formerfield_guide, demoted from tool to skill in v3 but re-added as a lightweight tool (0.6 × citation score + 0.4 × cosine similarity; no DeepSeek, no Pro quota). Pairs with the/field-guideskill for deeper orientation.co_author_graphandembed_text— shipped in the local v2.1.0 build but never published to npm; v3.0.0 is the first public release of both.
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."
Author discovery — "Who are the top researchers working on efficient LLM inference?"
Field orientation — "Give me an orientation report on sparse mixture-of-experts architectures."
Manual Installation
Claude Code
# Without API key (anonymous, 100 calls/day)
claude mcp add scholar-feed -- npx -y scholar-feed-mcp
# With API key (1,000 calls/day per account)
claude mcp add scholar-feed -e SF_API_KEY=sf_your_key_here -- npx -y scholar-feed-mcpCursor (.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 (8)
Core Search & Discovery
Tool | Description | Key Parameters |
| Semantic + keyword search with filters. Also does similar-paper discovery, citation-scoped search, and trending. |
|
| Get full paper details by arXiv ID. Also handles batch lookup and BibTeX export. |
|
| Citation graph (outgoing refs or incoming citations) |
|
| Extract results/experiments from LaTeX source |
|
Authors
Tool | Description | Key Parameters |
| Find researchers by topic/name query, or retrieve a profile by ID. |
|
| Co-authorship neighborhood for an author |
|
Embeddings
Tool | Description | Key Parameters |
| Get a 768-dim Gemini embedding for text (for HyDE and custom similarity) |
|
Research
Tool | Description | Key Parameters |
| Cheap retrieval orientation for a research area — top papers, subfields, open problems. No Pro quota. |
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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 |
| 30/min |
| 30/min |
| 30/min |
| 10/min |
| 20/min |
| 20/min |
| 30/min |
| 20/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).
Environment Variables
Variable | Required | Default | Description |
| No | — | Your Scholar Feed API key (starts with |
| 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 testsContributing
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 1,000 calls/day per account.
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.
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