Space Frontiers

Full-text retrieval for AI agents over peer-reviewed papers, books, patents, Wikipedia, Reddit, Telegram, and YouTube.

От сообществаРаботаетБез входаRU / СНГБесплатноТолько чтение

Что умеет

Spacefrontiers Search Documents: Search peer-reviewed papers, books, patents, and Wikipedia in the Space Frontiers `documents` index. Use when: the user asks about scientific concepts, technical metho
Spacefrontiers Search Social: Search Reddit, Telegram channels, and YouTube transcripts in the Space Frontiers `social` index. Use when: the user asks about news, recent events, announcements, ongoing
Spacefrontiers Fetch Document: Retrieve the full text, metadata, and references of one Space Frontiers document. Use when: you have a `source_uri` from a search hit and need the body to quote, summari

Какие данные видит

Нужен ли аккаунт

Не нужен: сервер работает без входа

Full-text retrieval for AI agents over peer-reviewed papers, books, patents, Wikipedia, Reddit, Telegram, and YouTube.

Four read-only tools:

search_documents
search_social
fetch_document
search_in_document — return canonical source URIs (DOI / arXiv / PMID / ISBN) for verbatim citation.

Список инструментов сервера (4)

Технические названия из tools/list. Нужны только разработчикам.

spacefrontiers_search_documents	Search peer-reviewed papers, books, patents, and Wikipedia in the Space Frontiers `documents` index. Use when: the user asks about scientific concepts, technical methods, prior art, citations, a DOI / ISBN / arXiv ID / PubMed ID, or wants peer-reviewed sources. Do not use when: the question is about news, current events, ongoing discussions, or social sentiment — call `spacefrontiers_search_social` instead. For general web pages or code, use a different MCP server. Examples: "crispr base editing efficiency", "doi:10.1038/s41586-023-06924-6", "isbn:9780262033848", "arxiv:2301.00001", "transformer attention scaling laws". Tips: - Run 2-6 parallel queries with varied phrasings (synonyms, narrower/broader terms). - Pass an empty `query` plus `filter_issns` to browse recent issues of a specific journal. - Use the returned `source_uri` verbatim with `spacefrontiers_fetch_document` for full text.
spacefrontiers_search_social	Search Reddit, Telegram channels, and YouTube transcripts in the Space Frontiers `social` index. Use when: the user asks about news, recent events, announcements, ongoing discussions, community opinions, or anything time-sensitive that wouldn't be in peer-reviewed literature. Do not use when: the question is about settled scientific knowledge, citations, or prior art — call `spacefrontiers_search_documents` instead. For general web search, use a different MCP server. Examples: "openai gpt-5 release date", "site:reddit.com/r/LocalLLaMA quantization", "@telegram_channel breaking news", "kubernetes 1.33 changes discussion". Tips: - Pair an empty `query` with `filter_uri_prefixes` to browse a subreddit or Telegram channel chronologically (combine with `filter_issued_after` for a time window). - For broad topics, also call `spacefrontiers_search_documents` in parallel for grounded sources.
spacefrontiers_fetch_document	Retrieve the full text, metadata, and references of one Space Frontiers document. Use when: you have a `source_uri` from a search hit and need the body to quote, summarize, or extract structured facts; or you want to walk the citation graph via `references` and `referenced_by`. Do not use when: you have not yet found the document — call a `spacefrontiers_search_*` tool first to obtain a real `source_uri`. Do not guess DOIs. Returns title, authors, abstract, content (truncated above ~100K chars), references with URIs, and up to 30 `referenced_by` documents you can fetch next. For documents over ~20K tokens prefer `spacefrontiers_search_in_document` to extract only the passages you need. Examples: `https://doi.org/10.1038/s41586-023-06924-6`, `arxiv:2301.00001`, `pmid:38019072`.
spacefrontiers_search_in_document	Find specific passages inside one Space Frontiers document without reading the whole body. Use when: the document is large (size > ~20K tokens shown in `content_size_tokens`) and you only need the parts relevant to a sub-question, e.g. "what error rates does this paper report?" against a 60-page review. Do not use when: you need the entire document to summarize or quote in full — call `spacefrontiers_fetch_document` instead. Do not call this without first obtaining a real URI via search. If no passage matches the query, the full document is returned in `fallback_full_document` so the caller never has to retry with a second tool call.