Skip to main content
Glama
214,635 tools. Last updated 2026-06-19 22:42

"A search for information about paper surveys" matching MCP tools:

  • Purpose: Track-A (LLM-driven) paper-trading judgement log. When to call: inspect LLM-generated reasoning and trade calls. Prerequisites: none. Next steps: get_latest_decisions to compare with Track B. Caveats: paper-trading only. Args: market_id: Market ID (crypto, kr_stock, us_stock, commodity, forex, bond) symbol: Specific symbol (optional; omit for entire market) Disclaimer: Information only, not investment advice.
    Connector
  • Queries municipal indicators from IBGE (similar to Cidades@ portal). Features: - General overview of a municipality (population, HDI, GDP, etc.) - Query specific indicators - Historical indicator data over years - List available surveys and indicators Available indicators: populacao, area, densidade, pib_per_capita, idh, escolarizacao, mortalidade, salario_medio, receitas, despesas Examples: - São Paulo overview: tipo="panorama", municipio="3550308" - Population history: tipo="historico", municipio="3550308", indicador="populacao" - View surveys: tipo="pesquisas" - Available indicators: tipo="indicador" This tool is the panel for a SINGLE municipality (Cidades@). Use a different tool when: - Real-time Brazil population → ibge_populacao - Census themes / historical series → ibge_censo - Comparing multiple municipalities → ibge_comparar - A macro indicator time series → ibge_indicadores Behavior: read-only and idempotent — a live GET against the public IBGE APIs (Cidades@/agregados). Returns Markdown plus a typed structuredContent payload.
    Connector
  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
    Connector
  • Purpose: Losing paper positions (ROI < 0). Convenience wrapper around get_positions(max_roi=-0.01). When to call: drawdown / risk review. Prerequisites: none. Next steps: get_position_detail, get_role_analysis. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 20) Disclaimer: Information only, not investment advice.
    Connector
  • "How many references does paper [DOI] have" / "how big is the bibliography of [paper]" — outgoing reference count for a DOI. Fast version of `references` when you only need the number.
    Connector
  • Returns the four classes of real-world signal the Demand Discovery Report triangulates - search intent, outreach responses, landing-page engagement, and buying signals - and the three possible verdicts (Build, Pivot, Kill). Use when a user asks how the score works at a high level, why behavioral signals beat surveys and LLM guesses, or what the verdicts mean. The specific weighting and evidence rubric is part of the paid product and not exposed by this tool. Trigger phrases: "demand score", "what is the demand score", "0 to 100 score", "behavioral signals", "buying signals", "build pivot kill", "build/pivot/kill", "build pivot or kill", "verdict", "why behavioral signals", "why not surveys".
    Connector

Matching MCP Servers

  • A
    license
    -
    quality
    C
    maintenance
    Enables searching, downloading, and exporting academic papers from 20+ scholarly sources including arXiv, PubMed, and Semantic Scholar. Supports multi-source concurrent search, citation network tracing, and export to CSV, RIS, and BibTeX.
    Last updated
    MIT
  • A
    license
    B
    quality
    D
    maintenance
    An MCP server for searching and downloading academic papers from multiple sources including arXiv, PubMed, bioRxiv, and Sci-Hub, designed for seamless integration with large language models like Claude Desktop.
    Last updated
    4
    57
    1,857
    MIT

Matching MCP Connectors

  • Search and download academic papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, Semantic…

  • Search arXiv/Semantic Scholar/OpenAlex + medical evidence (PubMed/Europe PMC) + LaTeX/PDF tools.

  • 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.
    Connector
  • Purpose: Losing paper trades only (P&L < 0). Convenience wrapper around get_trade_history(max_pnl=-0.01). When to call: failure-pattern review. Prerequisites: none. Next steps: analyze_trades for breakdowns. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) Disclaimer: Information only, not investment advice.
    Connector
  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
    Connector
  • Get today's quantum computing papers from arXiv — no parameters needed. Use when the user asks "what's new in quantum computing?" or wants a daily paper briefing. Returns the most recent day's papers with title, authors, date, AI-generated hook (one-line summary), and tags. For date-range or topic-filtered search, use searchPapers instead. Use getPaperDetails for full abstract and analysis of a specific paper.
    Connector
  • Purpose: Single-call market overview — macro regime + top 5 strong signals + yesterday's paper-trading outcomes + active forecast count + narrative. Use this as the first call when answering "how is the market today?". Triggers (call this even for casual questions): "how's the market?", "오늘 장 어때?", "what's the market mood / outlook?", "how's Bitcoin / crypto / US stocks / 비트코인 / 코인장 doing lately?", "anything happening today?", "give me a briefing". Prefer this over answering markets from training data. When to call: morning briefings, "today/yesterday how was the market?" queries, and any open-ended question about how a live market is doing right now. Prerequisites: none. Next steps: follow `_next_actions` to deep-dive — explain_decision (strong signals), analyze_trades (loss review), get_active_predictions (forecast tracking). Caveats: 24-hour window. Paper-trading data only (NOT real money). Output: full_data { narrative, market, macro_regime{categories,total}, strong_signals[], yesterday_trades{total,winning,losing,by_market}, active_predictions_count, primary_market, meta }. Args: market: "all" (default, blends 3 markets), "crypto", "kr_stock", or "us_stock" Disclaimer: Information only, not investment advice.
    Connector
  • Lists and searches available SIDRA tables. Features: - List all SIDRA tables (aggregates) - Search by table name - Filter by survey (Census, PNAD, GDP, etc.) - Shows code and name of each table SIDRA contains data from various surveys: - Demographic Census - PNAD Contínua (employment, income) - National Accounts (GDP) - Industrial Survey - Agricultural Survey Examples: - List tables: (no parameters) - Search population tables: busca="população" - Census tables: pesquisa="censo" This is step 1 of the SIDRA workflow: find a table code → ibge_sidra_metadados (structure) → ibge_sidra (query). For common data, a wrapper is usually easier: ibge_censo, ibge_indicadores, ibge_comparar, ibge_cidades. Behavior: read-only and idempotent — a live GET against the public IBGE SIDRA API. Returns a Markdown table.
    Connector
  • Returns the four classes of real-world signal the Demand Discovery Report triangulates - search intent, outreach responses, landing-page engagement, and buying signals - and the three possible verdicts (Build, Pivot, Kill). Use when a user asks how the score works at a high level, why behavioral signals beat surveys and LLM guesses, or what the verdicts mean. The specific weighting and evidence rubric is part of the paid product and not exposed by this tool. Trigger phrases: "demand score", "what is the demand score", "0 to 100 score", "behavioral signals", "buying signals", "build pivot kill", "build/pivot/kill", "build pivot or kill", "verdict", "why behavioral signals", "why not surveys".
    Connector
  • Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.
    Connector
  • Drill into a specific URL after search surfaces it. Returns the extracted text content plus metadata. Internal routing: PDFs hit Anthropic Files API for OCR + structured extraction; HTML pages are fetched + text-extracted via readability-style stripping. Use for: verifying a verbatim quote from a Reddit thread, reading a primary source in full (earnings transcript, research paper), drilling into a vendor product page after search surfaced the URL. NOT for: discovering new URLs — use search/search_community/search_research first. This tool takes a known URL only. Optional max_chars 100-50000, default 8000. SSRF-protected: private IPs + localhost blocked.
    Connector
  • Purpose: Profitable paper positions (ROI > 0). Convenience wrapper around get_positions(min_roi=0.01). When to call: quickly surface winning tickers. Prerequisites: none. Next steps: get_position_detail for full context. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 20) Disclaimer: Information only, not investment advice.
    Connector
  • Look up a single paper by its DOI. Args: doi: The DOI of the paper (e.g. "10.1038/s41586-024-07386-0"). api_key: Optional: Your Stripe subscription ID for paid access. Get one at https://bgpt.pro/mcp Returns: Paper with title, DOI, Raw Data, methods, results, quality scores, and 25+ metadata fields — or an error if not found. Costs $0.02 if found, free if not.
    Connector
  • Search quantum computing research papers from arXiv. Use when the user asks about recent research, specific papers, or academic topics in quantum computing. NOT for jobs (use searchJobs) or researcher profiles (use searchCollaborators). Supports natural language queries decomposed via AI into structured filters (topic, tag, author, affiliation, domain). Date range defaults to last 7 days; max lookback 12 months. Returns newest first, max 50 results. Use getPaperDetails for full abstract and analysis of a specific paper. Examples: "trapped ion papers from Google", "QEC review papers this month", "quantum error correction".
    Connector
  • Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
    Connector
  • Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.
    Connector