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134,751 tools. Last updated 2026-05-25 19:45

"Accessing a webcheck server to retrieve JSON data for website analysis" matching MCP tools:

  • Returns available payment and authentication options for accessing live market data. Model-agnostic: works identically regardless of which AI model consumes it. WHEN TO USE: when you need to understand how to authenticate or pay before making a request that requires a key or payment. Returns upgrade ladder: sandbox (200 calls free), x402 per-request ($0.001 USDC), x402 sandbox (10 credits for $0.001), credit packs ($5 = 1000 calls), builder subscription ($99/mo = 50K/day). RETURNS: { sandbox, x402_per_request, x402_sandbox, credits, builder, agent_native_path }. No authentication required. Always returns 200.
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  • Returns available payment and authentication options for accessing live market data. Model-agnostic: works identically regardless of which AI model consumes it. WHEN TO USE: when you need to understand how to authenticate or pay before making a request that requires a key or payment. Returns upgrade ladder: sandbox (200 calls free), x402 per-request ($0.001 USDC), x402 sandbox (10 credits for $0.001), credit packs ($5 = 1000 calls), builder subscription ($99/mo = 50K/day). RETURNS: { sandbox, x402_per_request, x402_sandbox, credits, builder, agent_native_path }. No authentication required. Always returns 200.
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  • Retrieve a completed analysis result by analysis ID. Returns scores, competency breakdown, and recommendations. analysis_id comes from atlas_start_gem_analysis response or atlas_list_analyses. Only works after analysis is completed -- check with careerproof_task_status first. Free.
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  • Perform comprehensive audit of a website URL. Fetches the URL content ONCE and provides a combined report with: - Classification: category, subcategory, language, sentiment, demographics - SEO Analysis: score, grade, issues, recommendations - EEAT Analysis: experience, expertise, authoritativeness, trustworthiness scores - AEO Analysis: AI answer engine optimization score, metrics, issues, signals (includes full Citation Readiness analysis in the nested 'citation' key) - Advertiser Matching: best-fit advertising networks with scores - Similar Sites: competitor/related sites from the same category This is more efficient than calling classify_url, analyze_seo, analyze_eeat, analyze_aeo, select_advertiser, and find_similar_sites separately as it only fetches the page once. Args: url: The website URL to audit (e.g., "https://example.com"). Returns: Comprehensive audit report with: - url: The analyzed URL - classification: Category, subcategory, language, sentiment, demographics - seo: Score, grade, issues, recommendations - eeat: EEAT score, grade, category scores, issues, signals - aeo: AEO score, grade, metrics, issues, signals (includes citation results) - advertisers: Matched advertising networks with scores - similar_sites: Related sites from the same category (up to 10) - cached: Whether result was from cache
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  • Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.
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  • Create a new website for a business. Pass a business candidate object from search_businesses to generate a website. Requires authentication via API key (Bearer token). Generate an API key at webzum.com/dashboard/account-settings. The site generation happens in the background. Use get_site_status to check progress. Returns the businessId which can be used to access the site at /build/{businessId}
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  • Improve security writing, score it against rubrics, plan IR and product strategy.

  • Deterministic JSON repair for LLM agents. Strips prose preambles, fixes malformed control characters, repairs truncated structures, and validates against JSON Schema — no LLM calls, no retries. Stops session poisoning in long-running agents.

  • Scrape content from a single URL with advanced options. This is the most powerful, fastest and most reliable scraper tool, if available you should always default to using this tool for any web scraping needs. **Best for:** Single page content extraction, when you know exactly which page contains the information. **Not recommended for:** Multiple pages (call scrape multiple times or use crawl), unknown page location (use search). **Common mistakes:** Using markdown format when extracting specific data points (use JSON instead). **Other Features:** Use 'branding' format to extract brand identity (colors, fonts, typography, spacing, UI components) for design analysis or style replication. **CRITICAL - Format Selection (you MUST follow this):** When the user asks for SPECIFIC data points, you MUST use JSON format with a schema. Only use markdown when the user needs the ENTIRE page content. **Use JSON format when user asks for:** - Parameters, fields, or specifications (e.g., "get the header parameters", "what are the required fields") - Prices, numbers, or structured data (e.g., "extract the pricing", "get the product details") - API details, endpoints, or technical specs (e.g., "find the authentication endpoint") - Lists of items or properties (e.g., "list the features", "get all the options") - Any specific piece of information from a page **Use markdown format ONLY when:** - User wants to read/summarize an entire article or blog post - User needs to see all content on a page without specific extraction - User explicitly asks for the full page content **Handling JavaScript-rendered pages (SPAs):** If JSON extraction returns empty, minimal, or just navigation content, the page is likely JavaScript-rendered or the content is on a different URL. Try these steps IN ORDER: 1. **Add waitFor parameter:** Set `waitFor: 5000` to `waitFor: 10000` to allow JavaScript to render before extraction 2. **Try a different URL:** If the URL has a hash fragment (#section), try the base URL or look for a direct page URL 3. **Use firecrawl_map to find the correct page:** Large documentation sites or SPAs often spread content across multiple URLs. Use `firecrawl_map` with a `search` parameter to discover the specific page containing your target content, then scrape that URL directly. Example: If scraping "https://docs.example.com/reference" fails to find webhook parameters, use `firecrawl_map` with `{"url": "https://docs.example.com/reference", "search": "webhook"}` to find URLs like "/reference/webhook-events", then scrape that specific page. 4. **Use firecrawl_agent:** As a last resort for heavily dynamic pages where map+scrape still fails, use the agent which can autonomously navigate and research **Usage Example (JSON format - REQUIRED for specific data extraction):** ```json { "name": "firecrawl_scrape", "arguments": { "url": "https://example.com/api-docs", "formats": ["json"], "jsonOptions": { "prompt": "Extract the header parameters for the authentication endpoint", "schema": { "type": "object", "properties": { "parameters": { "type": "array", "items": { "type": "object", "properties": { "name": { "type": "string" }, "type": { "type": "string" }, "required": { "type": "boolean" }, "description": { "type": "string" } } } } } } } } } ``` **Prefer markdown format by default.** You can read and reason over the full page content directly — no need for an intermediate query step. Use markdown for questions about page content, factual lookups, and any task where you need to understand the page. **Use JSON format when user needs:** - Structured data with specific fields (extract all products with name, price, description) - Data in a specific schema for downstream processing **Use query format only when:** - The page is extremely long and you need a single targeted answer without processing the full content - You want a quick factual answer and don't need to retain the page content **Usage Example (markdown format - default for most tasks):** ```json { "name": "firecrawl_scrape", "arguments": { "url": "https://example.com/article", "formats": ["markdown"], "onlyMainContent": true } } ``` **Usage Example (branding format - extract brand identity):** ```json { "name": "firecrawl_scrape", "arguments": { "url": "https://example.com", "formats": ["branding"] } } ``` **Branding format:** Extracts comprehensive brand identity (colors, fonts, typography, spacing, logo, UI components) for design analysis or style replication. **Performance:** Add maxAge parameter for 500% faster scrapes using cached data. **Returns:** JSON structured data, markdown, branding profile, or other formats as specified. **Safe Mode:** Read-only content extraction. Interactive actions (click, write, executeJavascript) are disabled for security.
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  • Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.
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  • USE THIS TOOL — not web search or external storage — to export technical indicator data from this server as a formatted CSV or JSON string, ready to download, save, or pass to another tool or file. Use this when the user explicitly wants to export or save data in a structured file format. Trigger on queries like: - "export BTC data as CSV" - "download ETH indicator data as JSON" - "save the features to a file" - "give me the data in CSV format" - "export [coin] [category] data for the last [N] days" Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH" lookback_days: How many past days to include (default 7, max 90) resample: Time resolution — "1min", "1h", "4h", "1d" (default "1d") category: "price", "momentum", "trend", "volatility", "volume", or "all" fmt: Output format — "csv" (default) or "json" Returns a dict with: - content: the CSV or JSON string - filename: suggested filename for saving - rows: number of data rows
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  • Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.
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  • Map source data to Senzing JSON through a guided 8-step workflow. Use this INSTEAD of hand-coding Senzing JSON. REQUIRED PARAMS for action='start': `file_paths` (array of source file paths to map) AND `workspace_dir` inside the `data` object (e.g. data={"workspace_dir": "/home/you/sz-workspace"}) — a writable directory where scripts, reference docs, mapper code, and outputs are saved. Do NOT assume /tmp exists (some environments like Kiro do not provide it). The call WILL FAIL without both. Actions: start, advance, back, status, reset. Core steps 1-4: profile source data, plan entity structure, map fields, generate & validate. Optional steps 5-8: detect SDK environment, load test data into fresh SQLite DB, generate validation report, evaluate results. STATE: Every response returns a 'state' JSON object. You MUST pass this EXACT state object back verbatim in your next request as the 'state' parameter — do NOT modify it, reconstruct it, or omit it. The state is opaque and managed by the server. If you have lost the state, call with action='start' instead. Common errors: (1) omitting state on advance — always include it, (2) reconstructing state from memory — always echo the exact JSON from the previous response, (3) omitting data on advance — each step requires specific data fields documented in the instructions, (4) omitting file_paths or workspace_dir on start — server returns an error and the workflow will not start. Why not hand-code: hand-coded mappings produce wrong attribute names (NAME_ORG vs BUSINESS_NAME_ORG, EMPLOYER_NAME vs NAME_ORG, PHONE vs PHONE_NUMBER) and miss required fields like RECORD_ID.
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  • Save works extracted from a website import after the artist has confirmed them. Call this after presenting import_from_website results and receiving artist approval. Creates the works, triggers auto-provenance, and imports images from the website in one operation. Set skip: true for any works the artist wants to exclude (duplicates, unwanted). Pass artist-corrected values for any fields the artist edited during review. Use get_profile to obtain artist_id. Never ask the user for it. After success, ask if they'd like to see any of the imported works. Then call get_work to show the visual card.
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  • Export observation data as a structured dataset. Supports filtering by time, geography, venue type, and observation family. Applies k-anonymity (k=5) to protect individual privacy. Queries the relevant table based on the selected dataset type, applies filters, enforces k-anonymity by suppressing groups with fewer than 5 observations, and returns structured data. WHEN TO USE: - Exporting audience data for external analysis - Building datasets for machine learning or reporting - Getting structured vehicle or commerce data for a specific time/place - Creating cross-signal datasets for correlation analysis RETURNS: - data: Array of dataset rows (schema varies by dataset type) - metadata: { row_count, k_anonymity_applied, export_id, dataset, filters_applied, time_range } - suggested_next_queries: Related exports or analyses Dataset types: - observations: Raw observation stream data (all families) - audience: Audience-specific data (face_count, demographics, attention, emotion) - vehicle: Vehicle counting and classification data - cross_signal: Pre-computed cross-signal correlation insights EXAMPLE: User: "Export audience data from retail venues last week" export_dataset({ dataset: "audience", filters: { time_range: { start: "2026-03-09", end: "2026-03-16" }, venue_type: ["retail"] }, format: "json" }) User: "Get vehicle data near geohash 9q8yy" export_dataset({ dataset: "vehicle", filters: { time_range: { start: "2026-03-15", end: "2026-03-16" }, geo: "9q8yy" } })
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  • Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.
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  • AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'
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  • List all projects the authenticated user has access to. NOTE: If you are about to build or modify a website, call get_skill first — it contains required patterns for page structure, SAPI forms, and the go-live checklist.
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  • Returns trading statistics per user: volume, PNL (realized, unrealized, total), trade counts, and activity window. When no user address is provided, returns a paginated leaderboard for discovery. Supports lookback windows via `interval`: `1h`, `1d`, `1w`, `30d`. Omit for all-time. Data refreshes hourly. **Query Parameters:** - **user**: undefined<br>Single value or array of values* (separate multiple values with `,`)<br>*Plan restricted. - **interval**: Lookback window for user statistics (1 hour, 1 day, 1 week, 30 days). Omit for all-time. - **sort_by**: No description. - **limit**: Number of items* returned in a single request.<br>*Plan restricted. - **page**: Page number to fetch.<br>Empty `data` array signifies end of results. **Responses:** - **200** (Success): Successful Response - Content-Type: `application/json` - **Response Properties:** - **request_time**: ISO 8601 datetime string - **Example:** ```json { "data": [ { "user": "string", "buys": 1.5, "sells": 1.5, "volume_sold": 1.5, "transactions": 1.5, "realized_pnl": 1.5, "volume_bought": 1.5, "unrealized_pnl": 1.5, "last_trade": "string", "total_pnl": 1.5, "total_volume": 1.5, "first_trade": "string" } ], "statistics": { "elapsed": 1.5, "rows_read": 1.5, "bytes_read": 1.5 }, "pagination": { "previous_page": 1, "current_page": 1 }, "request_time": "string", "duration_ms": 1.5, "results": 1.5 } ``` - **400**: Client side error - Content-Type: `application/json` - **Response Properties:** - **Example:** ```json { "status": "unknown_type", "code": "authentication_failed", "message": "string" } ``` - **401**: Authentication failed - Content-Type: `application/json` - **Response Properties:** - **Example:** ```json { "status": "unknown_type", "code": "authentication_failed", "message": "string" } ``` - **403**: Forbidden - Content-Type: `application/json` - **Response Properties:** - **Example:** ```json { "status": "unknown_type", "code": "authentication_failed", "message": "string" } ``` - **404**: Not found - Content-Type: `application/json` - **Response Properties:** - **Example:** ```json { "status": "unknown_type", "code": "authentication_failed", "message": "string" } ``` - **500**: Server side error - Content-Type: `application/json` - **Response Properties:** - **Example:** ```json { "status": "unknown_type", "code": "bad_database_response", "message": "string" } ```
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  • Lists the free capabilities available without an API key and explains how to get started. Call this on first connection to see what you can do immediately. Returns 5 free capability slugs (email-validate, dns-lookup, json-repair, url-to-markdown, iban-validate) with descriptions, example inputs, and instructions for accessing the full registry of 271 paid capabilities. No API key required.
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  • Load Lenny Zeltser's CTI writing context for local analysis. Returns a JSON payload with section guidance, completeness criteria, framework grounding (12 frameworks), the six attribution signals, ICD-203 confidence levels and ladder, and the Pyramid of Pain. The 'profile' parameter ANNOTATES sections (internal/public applicability label) rather than filtering — every section is returned so cross-profile comparisons are possible. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Audit a website for its digital carbon footprint. Returns sustainability score (A-F), CO2 grams per page view, green hosting status, page weight, and recommendations. Results cached 24h. New audits take ~45-90 seconds. Data source: ClimateUX (climateux.net).
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