Scholar Feed
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.
- Stimmen der NutzeriNoch keine BewertungenBewertungen starten in einem späteren Schritt zusammen mit Benutzerkonten
- Unsere Basischecksi3 von 3 bestandenAnhand öffentlicher Informationen geprüft; Code noch nicht gescannt
- NutzungiGanz neu↓ 84/Wo. · ★ –
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
- Basischecks: 3 von 3 bestanden
- Läuft auf dem Server des Entwicklers: Was du fragst, läuft über dessen Server.
- Kann 27 Dinge (Tools) search_papers, get_paper, get_citations, fetch_fulltext …
- Das trägst du selbst ein:
SF_API_KEY
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:
- Öffne Settings → Connectors
- Tippe auf Add custom connector
- Füge die Adresse unten ein und tippe auf Add
- Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
https://mcp.scholarfeed.org/mcp?src=mcp-registryOder 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-mcpTrag die leeren Werte ein, bevor du ihn startest.
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
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.
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
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:
- Öffne ChatGPT im Web → Settings → Connectors (Apps)
- Tippe auf Create oder Add (bei manchen Tarifen musst du zuerst Developer mode unter Advanced einschalten)
- Füge die Adresse unten ein, gib ihr einen Namen und speichere
- Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
https://mcp.scholarfeed.org/mcp?src=mcp-registryMenünamen 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
- 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_papersSearch 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_paperGet 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_citationsGet 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_fulltextRead 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_authorTwo-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_graphFind 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_textEmbed 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_orientationReturns 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_lineageReturns 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_paperSave 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_paperRemove 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_paperLike 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_libraryList 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_collectionsList 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_collectionCreate 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_collectionAdd 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_collectionRemove 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_watchCreate 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_watchesList 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_watchesPull 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_watchDelete 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_watchUpdate 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_watchDry-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_gapsFind 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_libraryAnswer 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_paperRecord 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_driftAnswers '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
Codebase Memory
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Exa
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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:
- 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 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:
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
| 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,
Nur der Anfang wird gezeigt; den Rest findest du im Repo