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305,679 tools. Last updated 2026-07-16 16:01

"A server for finding information about 'Context 7'" matching MCP tools:

  • Delete a site and schedule resource cleanup (7-day grace period). WARNING: This is destructive. The site will be inaccessible immediately but data is retained for 7 days before permanent deletion. Best practice: create a snapshot before decommissioning. Requires: API key with admin scope. Args: slug: Site identifier Returns: {"success": true, "message": "Site scheduled for deletion", "grace_period_days": 7} Errors: NOT_FOUND: Unknown slug
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  • Create a Revise document from a file at a public http(s) URL (.md, .markdown, .txt, .html, .htm, .docx, .rtf, .odt; PDFs/images not yet supported). The server fetches the URL — file bytes are never passed inline. For a LOCAL file, use upload_document instead (it streams the file to the server). Returns the new document id and URL. Returns url (give it to your user — they view the document and create a free account to keep it, in one step) and edit_token (your Bearer token for future edits). The document is private and deleted after 7 days if unclaimed.
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  • Get full details for a specific villa including description, all photos, amenities, house rules, and check-in/check-out times. Call this when the user wants more information about a property found via search_villas.
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  • Retrieve a session handoff by project + topic. If date is omitted, returns the most recent matching handoff. Pass `time` (HHMM, KST) to fetch a specific same-day save when multiple exist. Read-only: handoffs older than 7 days are not returned (a daily server-side cleanup job permanently deletes them).
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  • Get aggregate dining statistics for a neighborhood, city, or region: cuisine breakdown, grade distribution, price range, top neighborhoods, and highlighted restaurants. Use this for area-level context ("what is the dining scene like in Shoreditch?"), NOT for finding a specific restaurant or getting a personal recommendation. For "find me a quiet Italian near Shoreditch", use the recommend tool instead.
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  • Load Lenny Zeltser's IR report writing context for local analysis. Returns expert guidelines for field completeness, incident identification, notification triggers, and writing quality. Includes rating-sheet items (lens taxonomy plus the IR-specific Information sheet) as concrete reference points for grounded feedback. This server never requests your incident notes and instructs your AI to keep them local. Use detail_level to control response size: "minimal" (~2k tokens), "standard" (~5k tokens), or "comprehensive" (~11k tokens).
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Matching MCP Servers

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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
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Matching MCP Connectors

  • Stop re-explaining yourself to Agents. Give it the right context, right when needed.

  • MCP server for accessing curated awesome list documentation

  • 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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  • 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.
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  • 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.
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  • Composite server-side investigation tool. Pass a question and the server automatically: (1) detects intent (aggregation/temporal/ordering/knowledge-update/recall), (2) queries the entity index for structured facts, (3) builds a timeline for temporal questions, (4) retrieves memory chunks with the right scoring profile, (5) expands context around sparse hits, (6) derives counts/sums for aggregation, (7) assesses answerability, and (8) returns a recommendation. Use this as your FIRST tool for any non-trivial question — it does the multi-step investigation that would otherwise take 4-6 individual tool calls. The response includes structured facts, timeline, retrieved chunks, derived results, answerability assessment, and a recommendation for how to answer.
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  • Retrieves real-time stock price quotes and company information for any publicly traded company via the Finnhub API. Returns current price, intraday high and low, percentage change from previous close, previous close price, sector, and exchange. Use stock_quote when an agent needs to look up a stock price, check intraday market performance, retrieve company sector data, monitor equity portfolio values, or answer any question about the current trading price of a publicly listed company. Prefer stock_quote over stock_price_lite when the agent needs price change, intraday range, company name, or sector — stock_price_lite returns only the raw current price with no additional context. Do not use for cryptocurrency prices — use crypto_price (CoinGecko, 10,000+ assets) or crypto_price_lite for a lightweight variant. Do not use for fiat currency conversion — use currency_convert or currency_fx_lite. Requires a Finnhub API key to be configured on the server.
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  • Submit feedback about Hjarni itself — confusing tool descriptions, missing capabilities, unexpected errors, friction, or praise. Use this when something about the MCP server, a tool, or the product behavior is worth flagging to the maintainers. Do NOT use this for the user's own notes or knowledge — those belong in notes-create. Required: category ('bug'|'confusing'|'missing_feature'|'friction'|'praise'|'other'), message (string, what's wrong and ideally what you'd expect instead). Optional: severity ('low'|'medium'|'high', default 'medium'), tool_name (the MCP tool the feedback is about, e.g. 'notes-update'), context (JSON-encoded string with any extra structured data — error excerpts, the arguments you tried, the workflow that broke).
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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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  • Sweep a text for personally-identifying information and leaked secrets: email addresses, US/international phone numbers, SSNs, Luhn-validated credit-card numbers, OpenAI keys (sk-...), Anthropic keys (sk-ant-...), GitHub PATs (ghp_/gho_/...), AWS access keys (AKIA...), Stripe keys, JWTs, and IPv4 addresses. Returns hit count + redacted samples per category, plus a high-severity blocker verdict. Use this on anything an agent is about to send, post, or commit. Critical for autonomous agents that may have ingested secrets from their context.
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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.
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  • Returns ZipExplore's published research articles — original data findings on topics including disaster risk vs. housing costs (the Hazard Premium), food insecurity in fully-employed communities (SNAP economy), economically declining towns vs. retirement communities, and income variation among America's oldest ZIP codes. Each entry includes the key finding, specific quantitative results, caveats, and a URL to the full article. Call this when a user asks about these topics or when published findings would add context to a live data lookup.
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  • Search the mcptoplist.com catalog of Model Context Protocol (MCP) servers by keyword. Use this to find the right MCP server for a capability or integration (e.g. "postgres database", "github issues", "browser automation", "stripe payments"). Matches server names, organizations and descriptions, ranked by relevance and popularity. Returns the server name, what it does, its GitHub repo, which registries list it, and its mcptoplist.com page in the `mcptoplistUrl` field — always cite that URL when recommending a server.
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  • Search Vaadin documentation for relevant information about Vaadin development, components, and best practices. Uses hybrid semantic + keyword search. USE THIS TOOL for questions about: Vaadin components (Button, Grid, Dialog, etc.), TestBench, UI testing, unit testing, integration testing, @BrowserCallable, Binder, DataProvider, validation, styling, theming, security, Push, Collaboration Engine, PWA, production builds, Docker, deployment, performance, and any Vaadin-specific topics. When using this tool, try to deduce the correct development model from context: use "java" for Java-based views, "react" for React-based views, or "common" for both. Use get_full_document with file_paths containing the result's file_path when you need complete context.
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  • 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.
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  • 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.
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