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686,919 tools. Updated 2026-10-22 00:21

"A server for academic research" matching MCP tools:

  • Perform comprehensive research on a topic. Decomposes your query into sub-queries, searches and reads multiple sources in parallel, then synthesizes a structured report with citations. Best for open-ended or comparative questions that need coverage from many angles. For simple factual lookups, use search instead (optionally with include_answer=true for cheap synthesis). Costs 50 credits. Returns: query, report (structured markdown with citations), sources (array of {title, url, fetched}), sub_queries (the decomposed queries), credits_used, credits_remaining, usage (token counts). Args: query: The research question or topic topic: "general" (default) or "news" (prioritize recent news articles) freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD" max_sources: Maximum number of sources to use, 5-30 (default 20)
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  • Calculate what percentage one number is of another. Given a value and a total, returns the percentage, decimal form, and simplified fraction. For example, 3 out of 4 yields 75%, 0.75, and '3/4'. Commonly used for test scores, survey results, financial ratios, completion rates, and unit conversions. Chain with percentage_increase to compare successive measurements or use with test_grade for academic scoring.
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  • Multi-step deep research: search, scrape, enrich entities, and synthesize into a cited report. Returns a report (title, summary, sections, key findings, confidence) with numbered sources and the people and companies it found, enriched. Use for a question that needs many sources and a synthesized, cited answer. It takes far longer and costs more than search, which suits a quick fact. Cost: standard 10 credits, deep 20 credits, comprehensive 35 credits, charged only when a call succeeds. Options change it: include_analysis true +5, academic in source_types +2, enrich_entities false -3, synthesis false -5.
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  • Search published provider reviews by query, Review Score range, and rating availability; sort alphabetically or by displayed Review Score. Scores equally weight eligible source ratings on a 10-point scale and use an approximate academic conversion for BBB grades. Use get_provider_reviews for source-level evidence.
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  • Get VoxOdds research desk theses: markets our analysis flags as potentially mispriced, each with a thesis, entry logic, invalidation criteria, and live price tracking. Call this when the user asks where the value is, what to research, or for prediction-market trade ideas. Research framing only - not financial advice. Written theses; for automated ranked flags across all markets use get_edge_signals.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    面向 Codex、WorkBuddy 等 AI 工具的知你AI助手合并版 Skills,涵盖当前会话分诊、客户查询与画像、历史会话检索、客户分群和 API Key 用量查询,并连接个微、企微、视频号、微信小程序、公众号、服务号、微信客服、微信小店、抖音号、小红书、微博、网站及H5客服等渠道。
    MIT No Attribution
  • A
    license
    Not graded
    quality
    B
    maintenance
    这是面向智能运维场景的 MCP 工具服务,让 Agent 能够按需检索日志内容并获取主机与应用的监控指标数据。它把实时的日志与指标证据接入 Plan-Execute-Replan 诊断流程,从而支撑自动故障排查与根因分析。
    MIT

Matching MCP Connectors

  • Read a single research author by author UUID. Use this tool when a user wants profile details for a specific research author returned by another research tool. The response includes author metadata, biography fields, profile URL, and visible sectors associated with the author. Missing, inactive, non-author, and hidden-sector-only authors return a generic not-found error.
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  • Fetches a single SMI deep report by id. Research Bundles are deep-report products, so use this tool for a Research Bundle id too rather than constructing a research_bundle: reference for the generic fetch tool. Accepts product-prefixed ids: RB-11751 (Research Bundle) and DR-11751 (Deep Report) both resolve here.
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  • Creates a Deep Research task for comprehensive, single-topic research with citations. USE THIS for analyst-grade reports, NOT for batch data enrichment. Use Parallel Search MCP for quick lookups. After calling, share the URL with the user and STOP. Do not poll or check results unless otherwise instructed. Multi-turn research: The response includes an interaction_id. To ask follow-up questions that build on prior research, pass that interaction_id as previous_interaction_id in a new call. The follow-up run inherits accumulated context, so queries like "How does this compare to X?" work without restating the original topic. Note: the first run must be completed before the follow-up can use its context.
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  • Liveness and capability check for yieldsentinel (yieldsentinel.eth). Returns service status, schemaVersion, policyVersion, feature flags, and the list of available tools. May refresh research vintage via a yieldhunter health ping; a verdict still requires check_position. YH healthy ≠ YS ok. Use this first to verify connectivity, then call check_position with policyPreset treasury-conservative | balanced-research | rwa-selective (or explicit thresholds). Research estimates only — non-custodial; never holds keys or executes transactions. Example input: {}
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  • Intelligently match a free-text affiliation string (as found in academic paper bylines or grant records) to research organizations in the ROR registry. Pass the raw affiliation text exactly as it appears — e.g. "Dept. of Physics, Univ. of California, Berkeley, CA, USA" or "Max-Planck-Institut für Astronomie, Heidelberg". ROR's affiliation matching algorithm performs substring detection, name-variant lookup, and scoring to identify candidate organizations. Returns each candidate with: confidence score (0–1), a "chosen" boolean (the best single match), matching_type (e.g. SINGLE SEARCH, COMMON TERMS), and the organization's ROR ID, canonical name, type, and country. Ideal for metadata curation, ORCID affiliation disambiguation, funder acknowledgment normalization, and building organization-level research analytics from unstructured text.
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  • Explains the provenance of a named archive colour: documented fact vs computational derivation vs cultural interpretation, with confidence and citation format. This is one component of colour_passport, but also a standalone research tool for deep provenance work (museum, documentary, editorial). Use colour_passport for a general profile; call this directly for research workflows needing full source-chain detail.
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  • Explains the provenance of a named archive colour: documented fact vs computational derivation vs cultural interpretation, with confidence and citation format. This is one component of colour_passport, but also a standalone research tool for deep provenance work (museum, documentary, editorial). Use colour_passport for a general profile; call this directly for research workflows needing full source-chain detail.
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  • Explains the provenance of a named archive colour: documented fact vs computational derivation vs cultural interpretation, with confidence and citation format. This is one component of colour_passport, but also a standalone research tool for deep provenance work (museum, documentary, editorial). Use colour_passport for a general profile; call this directly for research workflows needing full source-chain detail.
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  • All 32 ResumeMD templates with a one-line description of each. The same Markdown renders in every template, so use this to recommend a look for the user (for example: tech for engineers, executive for leadership roles, academic for research CVs). Template ids are also valid input to render_resume_pdf.
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  • Search the web and academic sources together, for questions that straddle both. ⚠️ Parameters go in the **query string**: `query` (required), `max_num_results`, `as_ylo`/`as_yhi`. Returns a search `id` and `results[]`; **the entry shape varies by source** — every result has `title`, `link` and `snippet`, and academic ones additionally carry `authors` and `number_of_citations`, so treat those two as optional rather than assuming they are there. Measured at about 3 seconds. Use it when you do not know in advance which kind of source will answer. When you do, `post_scholar_search_web` or `post_scholar_search_scholar` is more predictable. Keep the `id` for `post_scholar_search_explain`. <!-- aisa-pricing:start --> Published reference price: $0.01 USD per successful request. Account-specific pricing and final settlement may differ. <!-- aisa-pricing:end -->
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  • "Find research datasets about [topic]" / "open data on [subject]" / "look up [field] datasets" — search research datasets registered in OpenAIRE (Zenodo, Dryad, Figshare, B2SHARE etc.). Use for finding open research data to reuse / cite.
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  • Search the Peptide Library research database by name, synonym or alias (fuzzy), optionally filtered by research category or research area. Returns short educational profiles with evidence level and the canonical Peptide Library URL. Use get_peptide_details for the full profile. No dosing information.
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  • Search Google Scholar for academic papers, citations, and scholarly articles. Returns results with titles, authors, publication info, citation counts, and links to PDFs. Use cites parameter to find papers citing a specific work, or cluster to find all versions of a paper. For US court opinions and case law, use google_scholar_cases instead.
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  • Assemble a cited, geographically grounded Wanderloop research package for a location. Queries Atlasemoji-approved historical, archival, academic, environmental, wildlife, and place-record providers through the same provider registry used by the Wanderloop application. Returns evidence records, provider execution status, citations, GeoJSON map features, and saved manifest links. This is evidence assembly, not an unsupported AI-written story.
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