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MCP server for searching 600,000+ CS/AI research papers with citation graphs, full text, embeddings, and BibTeX. Works w
Search 600,000+ CS/AI/ML research papers with LLM-generated novelty analysis, without leaving Claude Code, Cursor, or any MCP client. Built for researchers running a literature review where they already work: search, trace citations, pull full text, and export BibTeX in the same session.
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.
npx scholar-feed-mcp@latest init
This interactive wizard will:
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"
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."
The fastest path is npx scholar-feed-mcp@latest init, which auto-detects your client and writes the config. To set it up by hand, every client launches the same stdio server (npx -y scholar-feed-mcp@latest); only the config-file location and the wrapper key differ.
Claude Desktop (one-click) installs without editing any config: download the .mcpb bundle from the latest release and open it (or drag it into Settings > Extensions). The installer shows one optional field for a Scholar Feed API key (sf_...): leave it blank for anonymous mode (100 calls/day), or paste a free key from scholarfeed.org/settings for 1,000/day.
Claude Code takes a one-line command:
# Anonymous (100 calls/day)
claude mcp add scholar-feed -- npx -y scholar-feed-mcp@latest
# With an 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-mcp@latest
Every other client takes this standard JSON block:
{
"mcpServers": {
"scholar-feed": {
"command": "npx",
"args": ["-y", "scholar-feed-mcp@latest"]
}
}
}
To raise limits to 1,000 calls/day, add "env": { "SF_API_KEY": "sf_your_key_here" } to the server entry. Get a free key at scholarfeed.org/settings.
Drop that block into the right config file:
| Client | Config file | Notes |
|---|---|---|
| Cursor | .cursor/mcp.json (project) or ~/.cursor/mcp.json (global) | Restart Cursor. |
| Claude Desktop | macOS: ~/Library/Application Support/Claude/claude_desktop_config.json; Windows: %APPDATA%\Claude\claude_desktop_config.json | Settings → Developer → Edit Config, then restart. |
| Windsurf | ~/.codeium/windsurf/mcp_config.json | Cascade → MCP icon → Configure, then refresh. |
| Cline / Roo Code | cline_mcp_settings.json | MCP Servers sidebar icon → Configure. Cline and Roo Code share this format. |
| Gemini CLI | ~/.gemini/settings.json (or project .gemini/settings.json) | |
| LM Studio | ~/.lmstudio/mcp.json | Program tab → Install → Edit mcp.json. Follows Cursor's notation. |
| JetBrains (PyCharm / IntelliJ) | AI Assistant → MCP → Add → As JSON | Requires AI Assistant 2025.1+. |
A few clients need a different wrapper key or file format:
VS Code: GitHub Copilot (.vscode/mcp.json) uses a servers key and an explicit type, and needs Copilot agent mode. You can also run MCP: Add Server from the Command Palette.
{
"servers": {
"scholar-feed": {
"type": "stdio",
"command": "npx",
"args": ["-y", "scholar-feed-mcp@latest"]
}
}
}
Zed (settings.json) uses a context_servers key, and the "source": "custom" line is required (without it, Zed silently skips the entry).
{
"context_servers": {
"scholar-feed": {
"source": "custom",
"command": "npx",
"args": ["-y", "scholar-feed-mcp@latest"]
}
}
}
Continue uses YAML, with mcpServers as a list, in ~/.continue/config.yaml (global) or .continue/config.yaml (workspace).
mcpServers:
- name: scholar-feed
type: stdio
command: npx
args:
- "-y"
- scholar-feed-mcp@latest
Project-scoped (.mcp.json), to share the server across a repo:
{
"mcpServers": {
"scholar-feed": {
"command": "npx",
"args": ["-y", "scholar-feed-mcp@latest"],
"env": { "SF_API_KEY": "${SF_API_KEY}" }
}
}
}
Windows: for any JSON config above, use "command": "cmd" and "args": ["/c", "npx", "-y", "scholar-feed-mcp@latest"].
Scholar Feed is a standard stdio MCP server, so any other MCP-compatible client works with the standard block too.
| Tool | Description | Key Parameters |
|---|---|---|
search_papers | Semantic + keyword search with filters. Also does similar-paper discovery, citation-scoped search, and trending. | q, category, novelty_min, days, sort, anchor_paper_id, scope_to_citations_of, mode, method_category, task, dataset, contribution_type, task_category, cursor, limit |
get_paper | Get full paper details by arXiv ID. Also handles batch lookup and BibTeX export. | arxiv_ids, format, fields, verbose |
get_citations | Citation graph (outgoing refs or incoming citations) | arxiv_id, direction, limit, fields |
fetch_fulltext | Extract results/experiments from LaTeX source | arxiv_id |
| Tool | Description | Key Parameters |
|---|---|---|
find_author | Find researchers by topic/name query, or retrieve a profile by ID. | q, id, field, limit |
co_author_graph | Co-authorship neighborhood for an author | author_ids, window_years |
| Tool | Description | Key Parameters |
|---|---|---|
embed_text | Get a 768-dim Gemini embedding for text (for HyDE and custom similarity). Pro-only, so anonymous/free callers get a 403 pro_required. | text, task_type |
| Tool | Description | Key Parameters |
|---|---|---|
get_field_orientation | Cheap retrieval orientation for a research area: top papers, subfields, open problems. No Pro quota. | topic, limit |
get_foundational_lineage | Foundational work for a paper's niche via the citation graph (consensus-then-lift): niche_roots → field_level → discipline, with cited_by_in_niche evidence. Surfaces canonical anchors semantic search misses. No Pro quota. | anchor_paper_id, scope, generality_ceiling, limit |
SF_API_KEY)These MUTATE or read the authenticated user's account. The core read/search tools above work anonymously; these need a key.
| Tool | Description | Key Parameters |
|---|---|---|
save_paper | Bookmark a paper to your library (idempotent; feeds personalization). | arxiv_id |
unsave_paper | Remove a paper from your library (idempotent). | arxiv_id |
like_paper | "More like this" calibration signal for the For You feed (insert-only). | arxiv_id |
list_library | List your saved papers, newest first. | limit, page |
list_collections | List collections with paper counts. | (none) |
create_collection | Create a named collection (get-or-create; no error on duplicate). | name |
add_to_collection | Add a paper to a collection by name or id (also auto-saves). | arxiv_id, collection_name, collection_id |
remove_from_collection | Remove a paper from a collection (stays saved). | arxiv_id, collection_name, collection_id |
create_watch | Standing daily-evaluated saved search; get-or-create by name. Define it with a structured criteria filter (recommended) or a single seed selector. | name, novelty_min, criteria, recency_days, q, collection_name, collection_id, anchor_paper_id, scope_to_citations_of, author_id, category |
list_watches | List watches with summary, last_evaluated_at, and pending_hits. | (none) |
check_watches | Pull new matches since the last digest (read-only, idempotent). | watch_name, watch_id, limit |
update_watch | Edit a watch in place: rename, change novelty_min, or retarget its structured criteria (clears pending hits). Address by name or id. | name, watch_id, new_name, novelty_min, criteria, recency_days |
preview_watch | Dry-run a structured criteria filter over recent papers without creating a watch; returns match_count and a sample to tune before saving. Read-only. | criteria, recency_days |
delete_watch | Delete a watch by name or id (idempotent). | name, watch_id |
find_gaps | "What am I missing?" for a collection or topic: foundational + frontier work you haven't saved (read-only, Pro). | collection_name, collection_id, topic, scope, limit |
ask_library | "Answer from my saved set": a cited synthesis over your library or one collection, grounded only in papers you've saved (read-only). The inverse of find_gaps. Free 1/month, then Pro 200/day. | question, collection_name, collection_id, limit |
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.
| Endpoint | Limit |
|---|---|
search_papers | 30/min |
get_paper | 30/min |
get_citations | 30/min |
fetch_fulltext | 10/min |
find_author | 20/min |
co_author_graph | 20/min |
embed_text | 30/min |
get_field_orientation | 20/min |
get_foundational_lineage | 20/min |
find_gaps | 20/min |
ask_library | 10/min |
Responses include X-RateLimit-Limit, X-RateLimit-Remaining, and X-RateLimit-Reset headers.
Daily volume quota (separate from the per-minute limits above, counted per account across all your keys): 100 calls/day anonymous, 1,000/day with a free key, 10,000/day on Pro. The AI synthesis tools have their own limits: ask_library is 1/month free, then 200/day on Pro; find_gaps and embed_text are Pro-only (a 403 pro_required otherwise).
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, which is more stable than page numbers for large result sets).
| Variable | Required | Default | Description |
|---|---|---|---|
SF_API_KEY | No | (none) | Your Scholar Feed API key (starts with sf_). Without it, runs in anonymous mode (100 calls/day). |
SF_API_BASE_URL | No | Production URL | Override API base URL |
npm install
npm run build # Build to build/
npm run dev # Watch mode
npm run typecheck # Type check without emitting
npm test # Run tests
See CONTRIBUTING.md for guidelines.
"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.
Server shows as "failed" with no error — especially right after an update
The first launch (and the first launch after each new release) makes npx download the package. The published bin is a single self-contained file with no dependency tree to resolve, so this is fast — but on a slow link it can still outrun your client's start-up timeout, and the server then shows as "failed" with no detail. Fixes: (1) warm the cache by running it once in a terminal — npx -y scholar-feed-mcp@latest --version — then restart your client; (2) raise the MCP start-up timeout if your client supports it (Claude Code: MCP_TIMEOUT=60000). For the fastest, offline-capable launches, install once globally and point the config at it instead of npx:
npm install -g scholar-feed-mcp
# then in your MCP config: "command": "scholar-feed-mcp", "args": []
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
The config blocks above pin scholar-feed-mcp@latest, which re-resolves the newest version each launch. If you previously used an unpinned scholar-feed-mcp and are stuck on an old build: npx --yes scholar-feed-mcp@latest.
Windows: "command not found"
Use "command": "cmd" with "args": ["/c", "npx", "-y", "scholar-feed-mcp@latest"] in your MCP config.
Scholar Feed is a research-discovery engine for computer science and AI/ML papers, founded in 2025. It indexes 600,000+ papers from arXiv — ranked by novelty, citation velocity, and relevance — with LLM-generated summaries, a citation graph, author profiles, and full-text extraction. It is available as a website, a public REST API, and a Model Context Protocol (MCP) server that AI agents can call directly. This package (scholar-feed-mcp) is the open-source MCP server.
See our privacy policy.
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