Scholar Feed MCP Server

<p align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/logo-dark.png"> <img alt="Scholar Feed" src="assets/logo-light.png" width="140" height="140"> </picture> </p>

Scholar Feed MCP Server

Research paper search with ranking and citation tracking, for LLM engineering and academic research, without leaving Claude Code, Cursor, or any MCP client.

Most paper tools hand back a flat list. Scholar Feed ranks it: sort by relevance, by proven citation count, or by rising impact, then trace any paper's citation lineage forward and backward across 22M+ edges. 600k+ CS/AI/ML papers, updated daily, each with an LLM-generated summary and novelty score.

Scholar Feed indexes arXiv papers daily and ranks them on recency, citation velocity, institutional reputation, and code availability.

Quick Start

npx scholar-feed-mcp@latest 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 200 calls/month, enough for a typical research session. For a higher quota (500/month per account) plus your library — collections, saved papers and watches — 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."

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."

Installation

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 (200 calls/month), or paste a free key from scholarfeed.org/settings for 500/month.

Claude Code takes a one-line command:

# Anonymous (200 calls/month)
claude mcp add scholar-feed -- npx -y scholar-feed-mcp@latest

# With an API key (500 calls/month 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 the quota to 500 calls/month, 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:

<details> <summary><strong>OpenAI Codex, VS Code (GitHub Copilot), Zed, Continue, and project-scoped configs</strong></summary>

OpenAI Codex (~/.codex/config.toml, or $CODEX_HOME/config.toml if you set that) uses TOML, not JSON — the block above will not work. One file serves both the Codex CLI and the IDE extension.

[mcp_servers.scholar-feed]
command = "npx"
args = ["-y", "scholar-feed-mcp@latest"]
env = { SF_API_KEY = "sf_your_key_here" }

Drop the env line to run keyless at 200 calls/month. On Windows, if Codex cannot launch the server, use command = "cmd" with args = ["/c", "npx", "-y", "scholar-feed-mcp@latest"].

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}" }
    }
  }
}

</details>

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.

Available Tools (27)

Core Search & Discovery

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	Read a paper's text by section (abstract, introduction, related_work, method, results, conclusion, or all). Pass arxiv_ids to read up to 8 papers in one call; a paper that cannot be extracted comes back as a failed entry, not a failed call.	arxiv_id, arxiv_ids, sections

Authors

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

Embeddings

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

Research

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
check_drift	"Is the method I use superseded — and by what?" Critique receipts + benchmark-dominance edges over ~10 LLM builder-problem families. No Pro quota.	family, method, limit

Library, Collections, Watches & Gap Analysis (require 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 (includes your notes).	limit, page
annotate_paper	Record your verdict on a paper — why it matters, when to use it, why you ruled it out. Upserted; returned by list_library, so it is what a later session reads instead of re-deriving.	arxiv_id, note_text, action
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 20/month, then Pro 200/day.	question, collection_name, collection_id, limit

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
search_papers	30/min
get_paper	30/min
get_citations	30/min
fetch_fulltext (single paper)	10/min
fetch_fulltext (batch, 2-8 papers)	6/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.

Monthly volume quota (separate from the per-minute limits above, counted per account across all your keys): 200 calls/month anonymous (per IP), 500/month with a free key, 10,000/month on Pro. A smaller daily cap (100 / 200 / 2,000) sits underneath it as a burst guardrail so a runaway loop cannot spend a month in an hour; hitting it returns a 429 with scope: "burst" and leaves your monthly quota untouched. Read your remaining month from GET /v1/health (monthly_limit / usage_this_month) before a batch.

The AI synthesis tools have their own limits: ask_library is 20/month free, then 200/day on Pro; find_gaps is Pro-only (a 403 pro_required otherwise). embed_text needs an account of any tier — anonymous callers get a 403 account_required.

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, which is more stable than page numbers for large result sets).

Environment Variables

Variable	Required	Default	Description
SF_API_KEY	No	(none)	Your Scholar Feed API key (starts with sf_). Without it, runs in anonymous mode (200 calls/month).
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

"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 200 calls/month. Get a free API key at scholarfeed.org/settings for 500 calls/month per account, plus your library.

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.

About Scholar Feed

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.

• Website: https://www.scholarfeed.org
• npm: https://www.npmjs.com/package/scholar-feed-mcp
• REST API: https://api.scholarfeed.org/v1

Privacy

See our privacy policy.

License

MIT