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Scholar Feed

von YGao2005Version 3.20.0i★ –iComputer oder Cloud
Name in der Registryio.github.YGao2005/scholar-feed-mcp

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

Rank CS/AI/ML papers by citations, forecast impact, or code adoption; trace 23.2M citation edges.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Computer oder Cloud
  • Transport: stdio, Streamable HTTP
  • Kategorie: Suche & KI-Gedächtnis
  • Das musst du eintragen: SF_API_KEY

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

Als geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.

Du brauchst

  • Läuft in der CloudNichts zu installieren; die Verbindung läuft übers Internet
  • npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:

  1. Öffne Settings → Connectors
  2. Tippe auf Add custom connector
  3. Füge die Adresse unten ein und tippe auf Add
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Add2https://…3
https://mcp.scholarfeed.org/mcp?src=mcp-registry

Oder führ ihn auf deinem Computer aus

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

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

Führe das in deinem Terminal aus

claude mcp add --transport http scholar-feed 'https://mcp.scholarfeed.org/mcp?src=mcp-registry'

Oder führ ihn auf deinem Computer aus

claude mcp add scholar-feed --env SF_API_KEY=your-value -- npx -y scholar-feed-mcp

Trag die leeren Werte ein, bevor du ihn startest.

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "scholar-feed": {
      "url": "https://mcp.scholarfeed.org/mcp?src=mcp-registry"
    }
  }
}

Oder führ ihn auf deinem Computer aus

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

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

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "scholar-feed": {
      "type": "http",
      "url": "https://mcp.scholarfeed.org/mcp?src=mcp-registry"
    }
  }
}

Oder führ ihn auf deinem Computer aus

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "scholar-feed": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "scholar-feed-mcp"
      ],
      "env": {
        "SF_API_KEY": "your-value"
      }
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

ChatGPT verbindet sich nur mit Servern im Internet:

  1. Öffne ChatGPT im Web → Settings → Connectors (Apps)
  2. Tippe auf Create oder Add (bei manchen Tarifen musst du zuerst Developer mode unter Advanced einschalten)
  3. Füge die Adresse unten ein, gib ihr einen Namen und speichere
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Create2https://…3
https://mcp.scholarfeed.org/mcp?src=mcp-registry

Menünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Werte, die du selbst einträgst

  • SF_API_KEY geheim env
    Optional free API key from scholarfeed.org/settings. Anonymous callers get 200 requests/month; a free account raises that to 500/month and unlocks your library, and Pro is 10,000/month.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Tool-Namen und -Beschreibungen genau so, wie der Server sie am 9. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.

  • search_papers

    Search Scholar Feed's 600k+ CS/AI/ML paper corpus. Semantic (embedding) search by default, so it finds conceptually related work even when the wording differs. EVERY PARAMETER DOCUMENTS ITS OWN BEHAVIOUR AND COVERAGE LIMITS — read the ones you intend to use; this description cove

  • get_paper

    Get full details for one or more papers by arXiv ID. Pass a single-element array for one paper; pass multiple IDs to batch-fetch up to 50 papers in one call. Pass format='bibtex' to get a .bib citation entry (bibtex is single-paper only; for multi-paper bibtex, call repeatedly).

  • get_citations

    Get the citation graph for a paper, sorted by citing-paper rank_score (highest-impact first). 'citing' = outgoing references this paper cites; 'cited_by' = incoming citations from other papers. Default response is a lean 12-field shape per paper — pass verbose=true for the full 2

  • fetch_fulltext

    Read arXiv papers' actual text, by section. Section selection controls context cost: ask for the one or two you need, not whole papers — 'all' is ~13.5KB a paper, 8 of them ~108KB. Section labels are inferred: check `low_confidence_sections` before calling one the paper's own. So

  • find_author

    Two-mode author tool. Provide exactly one of q or id. Q-MODE (q=...): search for researchers by topic or name — uses embedding similarity for topics ('efficient LLM inference'), fuzzy matching for names ('Yann LeCun'). Returns a list of matching authors with author_id, name, h_in

  • co_author_graph

    Find the co-authorship neighborhood of one or more authors. Given a list of author_ids, returns edges {from, to, papers_count, last_collab_year} where 'from' is one of the input authors and 'to' is any co-author appearing on a shared paper within the window. Use for AC reviewer t

  • embed_text

    Embed a text string into a 768-dim Gemini Flash vector. Use for HyDE-style retrieval: (1) write a hypothetical short paper that would perfectly answer the user's query, (2) embed it with task_type='RETRIEVAL_DOCUMENT' (default — matches the corpus embedding side), (3) pass the re

  • get_field_orientation

    Returns CANDIDATE FOUNDATIONAL PAPERS for a research topic — cheap retrieval only, no synthesis. Ranks papers by a blend of citation count (0.6 weight, captures importance) and semantic similarity to your topic (0.4 weight). Use this to bootstrap a literature survey or get a fast

  • get_foundational_lineage

    Returns the FOUNDATIONAL WORK FOR A PAPER'S NICHE via the citation graph — the relative question ('what is foundational for THIS paper's specific sub-field', often itself only modestly cited) rather than the obvious global landmarks. Anchors on the paper, takes its embedding neig

  • save_paper

    Save a paper to the authenticated user's Scholar Feed library (bookmark). MUTATES the library and feeds the user's personalization — saved papers are the strongest signal in the For You feed and the email digest. Idempotent: calling it again on an already-saved paper leaves it sa

  • unsave_paper

    Remove a paper from the authenticated user's Scholar Feed library. MUTATES the library. Idempotent: removing a paper that isn't saved leaves it unsaved. Note: the saved library is a superset of all collections, so un-saving a paper ALSO removes it from every collection it was in.

  • like_paper

    Like a paper — a 'more like this' calibration signal that tunes the user's For You feed toward similar work. INSERT-only and idempotent (liking twice is a no-op, never un-likes). Distinct from save_paper: like expresses taste for ranking; save bookmarks for later reading. Require

  • list_library

    List the authenticated user's saved papers (their library), newest first. Read-only. Use this to review a reading list or to see what's already saved before saving more. Requires SF_API_KEY. SHAPE: agent callers get a lean record — `llm_summary` (~300 chars) INSTEAD of the abstra

  • list_collections

    List the authenticated user's collections (named groups of saved papers) with paper counts. Read-only. Use before add_to_collection to see existing collections. Requires SF_API_KEY.

  • create_collection

    Create a new named collection. MUTATES. If a collection with that name already exists, returns the existing one (get-or-create — never errors on duplicate). Use "/" to nest under a folder, e.g. "AgentOPA/Formal" — the folder is derived from the name, so there is no parent to crea

  • add_to_collection

    Add a paper to a collection, addressed by collection_id OR collection_name (get-or-create by name — no need to look up an id first). Nest with "/": collection_name "AgentOPA/Formal" files the paper under an "AgentOPA" folder. MUTATES: also auto-saves the paper to the library. Ide

  • remove_from_collection

    Remove a paper from a collection, addressed by collection_id OR collection_name. MUTATES (the paper stays in your library; it's only removed from this collection). Idempotent. Requires SF_API_KEY.

  • create_watch

    Create a standing watch — evaluated daily against newly-indexed papers, surfacing new matches via the email digest and via check_watches. MUTATES. Get-or-create by name (re-creating with an existing name returns it unchanged — never errors on duplicate). TWO forms: (1) the v2 STR

  • list_watches

    List the authenticated user's watches with name, a one-line definition summary, last_evaluated_at, and pending_hits (count of new matches since the last digest delivery). Read-only. Use before create_watch to see what's already tracked. Requires SF_API_KEY.

  • check_watches

    Pull new matching papers since the last digest delivery, in the same shape as search_papers results. Optionally scope to one watch by watch_name OR watch_id; omit both for all watches. Read-only and idempotent — does NOT advance any watermark (only digest delivery does), so it is

  • delete_watch

    Delete a watch, addressed by watch_id OR name. MUTATES. Idempotent: deleting a non-existent watch is a no-op (no error). To change a watch in place (rename / novelty_min / retarget criteria) use update_watch instead of delete-and-recreate. Requires SF_API_KEY.

  • update_watch

    Update an existing watch in place — rename, change novelty_min, or RETARGET its structured filter `criteria`. MUTATES. Address by watch_id OR name. Changing criteria replaces the definition and clears the watch's pending hits (so stale matches don't deliver); the next daily eval

  • preview_watch

    Dry-run a structured filter over recent papers WITHOUT creating a watch — the tuning loop. Returns {window_days, needs_similarity, match_count, sample} so you can iterate (add a category, raise min_novelty, switch the collection relation) before saving with create_watch. Structur

  • find_gaps

    Find important work you HAVEN'T saved, for a collection or topic — a 'what am I missing?' analysis. Returns two buckets: foundational_gaps (canonical citation-graph anchors in the niche, not in your library) and frontier_gaps (recent high-novelty work in the niche, not yet saved)

  • ask_library

    Answer a question using ONLY the papers you've saved — a synthesis over your library (or one collection) with inline [arXiv-ID] citations. The inverse of find_gaps (which finds important work you're MISSING): ask_library reasons over what you HAVE. Optionally scope to one collect

  • annotate_paper

    Record YOUR verdict on a paper — why it matters for your work, when to use it, or why you ruled it out. One note per paper, upserted (writing again replaces it), so it is safe to call repeatedly. Requires SF_API_KEY. WHY IT MATTERS: this note is the only thing that survives betwe

  • check_drift

    Answers 'for my problem, is the method I use superseded — and by what?' over a grounded, entity-resolved knowledge base of textual critique receipts + benchmark-dominance edges (no LLM call at query time). Call with a `family` (e.g. 'rag', 'peft', 'kvcache') and a `method` (e.g.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 9. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto YGao2005 bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • ✓ Bestanden

    Endpunkt antwortet

    Antwort in 255 ms (HTTP 200)

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Keine Anmeldung nötig

  • ✓ Bestanden

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Wir haben 27 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden

Im Vergleich mit anderen in Suche & KI-Gedächtnisi

  • Mehr Sterne als 0 % der anderen 5764 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 39 % der anderen 5764 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 5764 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Scholar Feed sicher?

Er hat 3 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Das musst du eintragen: SF_API_KEY

Läuft er auf meinem Computer oder in der Cloud?

Beides geht: Installiere ihn auf deinem Computer oder verbinde dich mit der Cloud-Version.

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (3.20.0) kam vor 2 Monaten in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Context7, Codebase Memory, Exa

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:↓ Downloads pro Wochei★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Context7

Up-to-date docs for AI agents

von upstashWeit verbreitet↓ 972.664/Wo.★ 64.224Aktualisiert vor 3 Tagen

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Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

von DeusDataWeit verbreitet↓ 17.962/Wo.★ 48.148Aktualisiert vor 23 Tagen

Läuft auf deinem Computer

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

von exa-labsWeit verbreitet★ 5213Aktualisiert vor 2 Monaten

Läuft in der Cloud✓ exa.ai

README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

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:

ClientConfig fileNotes
Cursor.cursor/mcp.json (project) or ~/.cursor/mcp.json (global)Restart Cursor.
Claude DesktopmacOS: ~/Library/Application Support/Claude/claude_desktop_config.json; Windows: %APPDATA%\Claude\claude_desktop_config.jsonSettings → Developer → Edit Config, then restart.
Windsurf~/.codeium/windsurf/mcp_config.jsonCascade → MCP icon → Configure, then refresh.
Cline / Roo Codecline_mcp_settings.jsonMCP 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.jsonProgram tab → Install → Edit mcp.json. Follows Cursor's notation.
JetBrains (PyCharm / IntelliJ)AI Assistant → MCP → Add → As JSONRequires AI Assistant 2025.1+.

A few clients need a different wrapper key or file format:

OpenAI Codex, VS Code (GitHub Copilot), Zed, Continue, and project-scoped configs

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}" } } } }

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
ToolDescriptionKey Parameters
search_papersSemantic + 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_paperGet full paper details by arXiv ID. Also handles batch lookup and BibTeX export.arxiv_ids, format, fields, verbose
get_citationsCitation graph (outgoing refs or incoming citations)arxiv_id, direction, limit, fields
fetch_fulltextRead 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
ToolDescriptionKey Parameters
find_authorFind researchers by topic/name query, or retrieve a profile by ID.q, id, field, limit
co_author_graphCo-authorship neighborhood for an authorauthor_ids, window_years
Embeddings
ToolDescriptionKey Parameters
embed_textGet 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
ToolDescriptionKey Parameters
get_field_orientationCheap retrieval orientation for a research area: top papers, subfields, open problems. No Pro quota.topic, limit
get_foundational_lineageFoundational 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.

ToolDescriptionKey Parameters
save_paperBookmark a paper to your library (idempotent; feeds personalization).arxiv_id
unsave_paperRemove 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_libraryList your saved papers, newest first (includes your notes).limit, page
annotate_paperRecord 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_collectionsList collections with paper counts.(none)
create_collectionCreate a named collection (get-or-create; no error on duplicate).name
add_to_collectionAdd a paper to a collection by name or id (also auto-saves).arxiv_id, collection_name, collection_id
remove_from_collectionRemove a paper from a collection (stays saved).arxiv_id, collection_name, collection_id
create_watchStanding 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_watchesList watches with summary, last_evaluated_at, and pending_hits.(none)
check_watchesPull new matches since the last digest (read-only, idempotent).watch_name, watch_id, limit
update_watchEdit 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_watchDry-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_watchDelete 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,

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