Lune Research
Search peer-reviewed papers and research methodology guidance from your AI agent.
| Endpoint | https://mcp.luneresearch.com (streamable-http) |
|---|---|
| Registry version | 3.0.1 |
| Now | 13 tools · grade F (26) · pin ts_431f4d9fd62e2ae0dd96329cb1722cb9 · protocol 2025-06-18 |
| First / last listed | 2026-11-11 02:01 UTC / 2026-11-11 02:01 UTC |
| Grade over time | 2026-11-11: F (26), 13 tools |
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Tools: search_papers search_papers_many get_paper_fulltext get_paper_citations list_conferences get_conference_papers search_related_papers extract_from_papers verify_claims gather_evidence search_research_guidance get_research_guidance_doc send_feedback
search_papers | Searches full-text, peer-reviewed papers from top-tier venues. Use for questions about academic papers, research topics, literature reviews, surveys, “what's been published on X”, named methods, or any claim that should be backed by a peer-reviewed citation. Returns each paper's metadata and the passages that matched. Hybrid semantic + lexical search over titles, abstracts, and full text. Phrase t params: query*, conference, year, limit, offset, sort_by, year_min, year_max, venues, detail |
search_papers_many | Use for a LITERATURE SWEEP or survey: a research question broad enough to need several angles, e.g. "what's been done on X", a related-work section, or a state-of-the-field summary. One call returns one merged, ranked list of the papers the angles found, with the passages that matched. For a single focused question, use `search_papers` instead. Runs 1 to 25 query variants in ONE call and gets back params: queries*, conference, year, year_min, year_max, venues, limit*, detail* |
get_paper_fulltext | Use this when the user asks “what does the methods/results section say”, wants to quote a specific section, or when the abstract isn't enough to verify a claim. Heavy: only call once a paper looks relevant from `search_papers`, `search_related_papers`, or `get_paper_citations`. `format=markdown` returns one rendered document; `format=json` returns a structured section list. Pass `sections` (case-i params: paper_id*, format, sections |
get_paper_citations | Use this when the user asks “what does this paper build on”, “what built on this”, traces influence chains, asks for follow-up work, or wants the lineage of an idea. `direction=cited_by` returns indexed papers that cite this one; `direction=cites` returns this paper's parsed references (which may or may not be in the corpus). Each edge carries `contexts`, the citing sentences with their section, w params: paper_id*, direction, limit, offset |
list_conferences | Use this when the user asks “what conferences does Lune track”, “is venue X covered”, or wants a category-level browse (e.g. AI/ML, security, databases, software/systems). Pass `category` as a keyword (`ai`, `security`, ...) to narrow; it matches the conference's research area. params: category |
get_conference_papers | Use this when the user asks for papers from a specific conference (optionally a year), e.g. “most-cited NeurIPS 2024 papers”, “show me CCS 2025 accepted papers”, or “what's new in security at IEEE S&P this year”. `sort` is `recency` (newest first, default) or `citations` (most-cited first); page with `limit` / `offset`. params: conference*, year, limit, offset, sort |
search_related_papers | Given a paper_id, return the most semantically similar papers by embedding distance, NOT by citation links. Use for “more papers like this one” / “adjacent work on the same topic”. For papers this one cites or that cite it, use `get_paper_citations` instead. Each hit carries metadata, abstract, the closest non-abstract matched chunk as `contexts`, and a `similarity` score (0..1, higher is nearer). params: paper_id*, limit |
extract_from_papers | Pull a structured table out of up to 50 papers in ONE call: you define the columns (`fields`: each a snake_case `name`, a `type`, and an optional `description`) and an `instruction`, and the server reads each paper's full text and returns one typed row per paper. Use this when you need the SAME facts across many papers, e.g. "dataset, model size, and reported accuracy for each of these papers": on params: paper_ids*, fields*, instruction*, sections |
verify_claims | Fact-check 1 to 25 natural-language claims against Lune's peer-reviewed corpus in ONE call. For each claim the server retrieves the most relevant passages and an LLM judges the claim ONLY against those passages (never outside knowledge), returning one verdict per claim: `supported`, `unsupported`, or `insufficient_evidence`. Use this to ground a draft before you assert it, to vet a user's claim, o params: claims*, context, conference, year, year_min, year_max, venues |
gather_evidence | Use for a multi-part research task when you need to know whether your gathered evidence is SUFFICIENT, what is still MISSING, and what to search next, without the tool writing the answer. Pass the goal in `task` and your first search angles in `queries`; the server runs one corpus search per angle, decomposes the task into evidence requirements (or use your own via `requirements`), and returns eac params: task*, queries*, requirements, draft, max_iterations*, max_total_queries, conference, year, year_min, year_max, venues |
search_research_guidance | Use before recommending experimental design, ablation strategy, evaluation metrics, baselines, reproducibility, paper structure, related-work organisation, venue choice, response-to-reviewers, scientific writing, or methodology in general. Searches the Lune guidance corpus, curated from senior researchers, reproducibility checklists, venue-reviewer guidance, and author tutorials, so methodology ad params: query*, limit |
get_research_guidance_doc | Use this AFTER `search_research_guidance` when you need the full text of a guidance document (not just the matched excerpt), for example to quote a passage or follow a checklist end-to-end. Pass the `doc_id` from a search hit. params: doc_id* |
send_feedback | Sends the user's feedback about Lune to the Lune team. Use it when the user says something about Lune itself (papers it missed, results that did not fit, an error, something that helped, an idea): offer to pass it on, show the user the message you would send, and call this only after they agree. Set `allow_training` only if they also agreed that Lune may train models on it, after telling them they params: category*, message*, allow_training |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.