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187,022 tools. Last updated 2026-06-10 06:36

"A server for finding finance information" matching MCP tools:

  • Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search first to find valid names.
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  • Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")
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  • List BIS dataflow refs we have pre-vetted, grouped by topic (rates, fx, banking, debt, credit, property, derivatives, finance). Use the flow_ref with fetch_dataset. For everything else use search_dataflows or browse https://stats.bis.org.
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  • Fetch the full Yahoo Finance profile for a stock, ETF, mutual fund, crypto, or index. Returns name, sector, industry, market cap, P/E ratio, 52-week range, beta, dividend yield, description, and 60+ other metadata fields. Use this tool when: - You need a quick summary of what a company or fund is and its valuation - You want sector/industry classification for a ticker - You need current price metadata like market cap, float, or short ratio Works for: stocks (AAPL), ETFs (SPY), mutual funds (VFINX), crypto (BTC-USD), indices (^GSPC), forex (EURUSD=X). Source: Yahoo Finance via yfinance. No API key required.
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  • Fetch historical OHLCV price series for any ticker: stocks (AAPL, SAP.DE, 7203.T), ETFs, indices, commodities (GC=F for gold) or cryptocurrencies (BTC-USD). Returns a full date-indexed series of open/high/low/close/volume plus pre-computed statistics: total return, annualised return (CAGR), annualised volatility, max drawdown and Sharpe estimate (rf=4%). Automatically detects crypto tickers (→ CoinGecko) vs traditional assets (→ Yahoo Finance primary, Stooq fallback). Adjusts for dividends and splits when adjusted=true (default). Use cases: backtesting, factor analysis, performance attribution, charting, financial modelling. Sources: Yahoo Finance, CoinGecko, Stooq. All keyless. Optional env: AICI_RESEARCH_PROXY_URL for Bright Data routing (lifts Yahoo 429), TWELVE_DATA_API_KEY for higher Twelve Data quota.
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  • Top Hyperliquid perps ranked by absolute funding rate, with OI and annualized yield. Useful for finding the most overcrowded longs/shorts and carry opportunities.
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  • Get stock quotes, financial statements, market data, and company analysis from Yahoo Finance via MCP.

  • Financial benchmarks: yield curve, FX, WACC, M&A multiples, PE returns, and bank capital ratios.

  • Run a UK property development scheme viability appraisal. Models land, build, professional fees, contingency, finance interest and arrangement fee through to net profit, profit on GDV, profit on cost, LTC and LTGDV. Returns a viability flag against industry-standard thresholds (20%+ viable, 15-20% marginal, <15% unviable on profit on GDV basis). Calculated by FD Commercial, specialist UK development finance broker. Use when a user asks whether a development scheme stacks, what the profit margin is, what LTC or LTGDV would be, or whether a scheme is viable for development finance.
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  • Find info about notable/historic landmarks, towns, and remarkable sites near a coordinate. USE FOR: - "What's near Predjama Castle?" - "Notable landmarks around Ljubljana center" - "Tell me about places near 46.05, 14.51" - Finding historic, cultural, or geographic summaries for an entire area at once. - DO NOT iterate over the results to query individual items again. - One call is sufficient to answer the user's broad geographic inquiry. Combine the results into a single comprehensive summary for the user immediately. NOT FOR: directions, finding specific cafes/shops, raw geocoding.
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  • Query vulnerabilities for multiple packages in one call — the primary tool for dependency audits, SBOM scanning, and lockfile triage. Pass an array of {name, ecosystem, version} tuples (up to 1000). Each entry in the response corresponds positionally to the input. Each finding includes CVE aliases for chaining to nist-nvd-mcp-server for CVSS scoring. Invalid ecosystem strings are rejected before querying — call osv_list_ecosystems to validate.
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  • Fetch historical OHLCV price series for any ticker: stocks (AAPL, SAP.DE, 7203.T), ETFs, indices, commodities (GC=F for gold) or cryptocurrencies (BTC-USD). Returns a full date-indexed series of open/high/low/close/volume plus pre-computed statistics: total return, annualised return (CAGR), annualised volatility, max drawdown and Sharpe estimate (rf=4%). Automatically detects crypto tickers (→ CoinGecko) vs traditional assets (→ Yahoo Finance primary, Stooq fallback). Adjusts for dividends and splits when adjusted=true (default). Use cases: backtesting, factor analysis, performance attribution, charting, financial modelling. Sources: Yahoo Finance, CoinGecko, Stooq. All keyless. Optional env: AICI_RESEARCH_PROXY_URL for Bright Data routing (lifts Yahoo 429), TWELVE_DATA_API_KEY for higher Twelve Data quota.
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  • 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.
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  • Run a UK buy-to-let ICR stress test. Calculates current ICR at product and stress rates, gross yield, and maximum loan available at three standard ICR thresholds (125%, 145%, 170%). Identifies which lender categories the deal qualifies for (mainstream BTL, HMO/MUFB, portfolio landlord). Ownership-aware: personal name uses 5.5% stress rate; limited company uses max of product rate or 5.5%. Calculated by FD Commercial, specialist UK property finance broker. Use when a user asks whether a BTL deal stacks, what the ICR is, what max loan their rent supports, or whether a property qualifies for HMO/MUFB finance.
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  • Search the Tonzar B2B catalog of 160,000+ Russian industrial, medical, and agricultural products. Returns matching products with prices, suppliers, and specs. Use for finding Russian equipment for export.
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  • Run a UK property development scheme viability appraisal. Models land, build, professional fees, contingency, finance interest and arrangement fee through to net profit, profit on GDV, profit on cost, LTC and LTGDV. Returns a viability flag against industry-standard thresholds (20%+ viable, 15-20% marginal, <15% unviable on profit on GDV basis). Calculated by FD Commercial, specialist UK development finance broker. Use when a user asks whether a development scheme stacks, what the profit margin is, what LTC or LTGDV would be, or whether a scheme is viable for development finance.
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  • IMPORTANT: Prefer this over multiple sequential search calls when you have 2–5 independent queries. Saves context window space by returning all results in a single tool call. ## When to use Use batch_search instead of multiple sequential search calls when you have 2–5 independent queries. 🏆 PRIMARY use case: After get_sub_domains(domains=[...]) returns sub_domains across multiple domains, use batch_search to send one query per sub_domain in parallel. This is more efficient than sequential per-domain search calls. Also useful for ambiguous / fuzzy queries within a single domain: after get_sub_domains, use batch_search to explore multiple sub_domains in parallel. ## Constraints - Maximum 5 queries per call - Each query item follows the search tool parameter structure (query is required; domain, sub_domain, sub_domain_params are optional. For general queries, omit all domain fields. For vertical queries, domain + sub_domain + sub_domain_params MUST come from get_sub_domains(domain=<domain>) output — same rules as the search tool) - Queries run in parallel; a single query failure does not block others - REQUIRED PARAMS: Same rule as search — when a required param from get_sub_domains is not applicable, pass it as an empty string (key: ""). Never skip required params. ## Examples ### Single-domain batch (multiple sub_domains) Instead of: search(query="latest TSLA earnings", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA stock forecast", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA analyst rating", domain="finance", sub_domain="finance.us_stock") Use: batch_search(queries=[{query:"latest TSLA earnings", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA stock forecast", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA analyst rating", domain:"finance", sub_domain:"finance.us_stock"}]) ### Multi-domain batch (after get_sub_domains with multiple domains) After: get_sub_domains(domains=["finance", "health", "legal"]) Use: batch_search(queries=[ {query:"AI regulation impact on healthcare stocks 2025", domain:"finance", sub_domain:"finance.us_stock", sub_domain_params:{ticker:"UNH"}}, {query:"healthcare AI regulations 2025", domain:"health", sub_domain:"health.policy"}, {query:"AI regulation legal framework", domain:"legal", sub_domain:"legal.legislation"}]) ### Hybrid: general + vertical in parallel (universal pattern for any borderline query) Use this whenever you are unsure if the query is pure encyclopedia or domain-specific — fire BOTH channels in batch_search: batch_search(queries=[ {query:"..."}, // general — no domain {query:"...", domain:"...", sub_domain:"..."}]) // vertical channel(s) This applies universally: classical texts, financial concepts, legal theories, historical events, scientific discoveries, medical topics — any query where domain knowledge could enrich the encyclopedia answer.
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  • List podcasts in one or more Podcast Index categories, ordered by most-recently-updated. Use when the user wants to discover podcasters in a vertical without a specific keyword — e.g. "finance podcasters", "crypto shows", "marketing podcasts". For keyword + vertical, use search_podcast with cat= instead. Costs 1 credit.
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  • Get content recommendations for an AWS documentation page. ## Usage This tool provides recommendations for related AWS documentation pages based on a given URL. Use it to discover additional relevant content that might not appear in search results. URL must be from the docs.aws.amazon.com domain. ## Recommendation Types The recommendations include four categories: 1. **Highly Rated**: Popular pages within the same AWS service 2. **New**: Recently added pages within the same AWS service - useful for finding newly released features 3. **Similar**: Pages covering similar topics to the current page 4. **Journey**: Pages commonly viewed next by other users ## When to Use - After reading a documentation page to find related content - When exploring a new AWS service to discover important pages - To find alternative explanations of complex concepts - To discover the most popular pages for a service - To find newly released information by using a service's welcome page URL and checking the **New** recommendations ## Finding New Features To find newly released information about a service: 1. Find any page belong to that service, typically you can try the welcome page 2. Call this tool with that URL 3. Look specifically at the **New** recommendation type in the results ## Result Interpretation Each recommendation includes: - url: The documentation page URL - title: The page title - context: A brief description (if available)
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  • Use when valuing a business, setting hurdle rates, or benchmarking discount rates for M&A analysis or capital allocation. WACC benchmarks by sector and market cap tier from Damodaran annual dataset — used for DCF valuation, M&A pricing, board approval, and capital allocation. The most cited public finance benchmark. Updated January annually.
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  • Fetch historical OHLCV price series for any ticker: stocks (AAPL, SAP.DE, 7203.T), ETFs, indices, commodities (GC=F for gold) or cryptocurrencies (BTC-USD). Returns a full date-indexed series of open/high/low/close/volume plus pre-computed statistics: total return, annualised return (CAGR), annualised volatility, max drawdown and Sharpe estimate (rf=4%). Automatically detects crypto tickers (→ CoinGecko) vs traditional assets (→ Yahoo Finance primary, Stooq fallback). Adjusts for dividends and splits when adjusted=true (default). Use cases: backtesting, factor analysis, performance attribution, charting, financial modelling. Sources: Yahoo Finance, CoinGecko, Stooq. All keyless. Optional env: AICI_RESEARCH_PROXY_URL for Bright Data routing (lifts Yahoo 429), TWELVE_DATA_API_KEY for higher Twelve Data quota.
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  • Find associations similar to a given association based on category (objet_social) and geographic proximity. Returns nearby associations in the same activity category within a specified radius. Useful for discovering related organizations or finding alternatives in the same field.
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