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306,474 tools. Last updated 2026-07-25 10:38

"A server for finding information about Drupal, the open-source content management system" matching MCP tools:

  • Shows HTML content on a display: menus, dashboards, welcome pages, schedules or any custom design. slot 'live' (default) replaces the current content; slot 'idle' stores the default/fallback content shown when nothing live is active (idle requires admin scope). Always pass a short description so later content reads stay meaningful. Exactly one of html or base64_html. For external web pages use send_url; to edit current content call read_display_html first. For polished results load prompt render_premium_display_html or resource agentview://public/design-system. Requires content scope.
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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.
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  • Upload and normalize a FINISHED, ready-to-mail document to PDF. Choose this when the content is final and IDENTICAL for every recipient — including when you mail the same letter to many people (just quote/pay once per recipient with the same documentId). The exact bytes you give are what gets printed. Use create_template instead only when the content must vary per recipient via {{fields}}. Returns a documentId, the stored page count, byte size, and source format. Free; no payment required. Provide the document EXACTLY ONE way: `content` (inline text, for html/markdown/text), `contentBase64` (base64-encoded binary, for pdf/docx/image), or `url` (a publicly reachable URL the server fetches). Supplying none, or more than one, is an error. Maximum upload size is 31457280 bytes (~30 MB); output page size is US Letter. Any `{{...}}` text is printed LITERALLY here — it is NOT treated as a merge field. If you want personalized mail merge across recipients, use `create_template` instead. Reserved address zone: a recipient address block is printed over the top ~3 inches of page 1, so the server reserves that space for you automatically. For text/html/markdown/docx, page-1 content is pushed below the block (content may therefore flow onto an additional page); for pdf and image inputs, a blank first page is prepended. As a result the returned page count — and the selected-provider cost behind the resulting quote — can be higher than your source document (e.g. a single-page PDF is stored as 2 pages). You do NOT need to leave the top of your document blank yourself. See the postagent://formats resource for per-format details.
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  • Reads the raw HTML source currently shown on a display so you can inspect or edit it and push it back with send_html. content_type 'idle' reads the default/fallback content instead. Responses are windowed for large documents: max_bytes (default 51200) and offset page through the source; the result reports totalBytes and truncated. Not for visual previews (use get_display_preview_url). Requires content scope.
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  • Upload and normalize a FINISHED, ready-to-mail document to PDF. Choose this when the content is final and IDENTICAL for every recipient — including when you mail the same letter to many people (just quote/pay once per recipient with the same documentId). The exact bytes you give are what gets printed. Use create_template instead only when the content must vary per recipient via {{fields}}. Returns a documentId, the stored page count, byte size, and source format. Free; no payment required. Provide the document EXACTLY ONE way: `content` (inline text, for html/markdown/text), `contentBase64` (base64-encoded binary, for pdf/docx/image), or `url` (a publicly reachable URL the server fetches). Supplying none, or more than one, is an error. Maximum upload size is 31457280 bytes (~30 MB); output page size is US Letter. Any `{{...}}` text is printed LITERALLY here — it is NOT treated as a merge field. If you want personalized mail merge across recipients, use `create_template` instead. Reserved address zone: a recipient address block is printed over the top ~3 inches of page 1, so the server reserves that space for you automatically. For text/html/markdown/docx, page-1 content is pushed below the block (content may therefore flow onto an additional page); for pdf and image inputs, a blank first page is prepended. As a result the returned page count — and the selected-provider cost behind the resulting quote — can be higher than your source document (e.g. a single-page PDF is stored as 2 pages). You do NOT need to leave the top of your document blank yourself. See the postagent://formats resource for per-format details.
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  • Upload and normalize a FINISHED, ready-to-mail document to PDF. Choose this when the content is final and IDENTICAL for every recipient — including when you mail the same letter to many people (just quote/pay once per recipient with the same documentId). The exact bytes you give are what gets printed. Use create_template instead only when the content must vary per recipient via {{fields}}. Returns a documentId, the stored page count, byte size, and source format. Free; no payment required. Provide the document EXACTLY ONE way: `content` (inline text, for html/markdown/text), `contentBase64` (base64-encoded binary, for pdf/docx/image), or `url` (a publicly reachable URL the server fetches). Supplying none, or more than one, is an error. Maximum upload size is 31457280 bytes (~30 MB); output page size is US Letter. Any `{{...}}` text is printed LITERALLY here — it is NOT treated as a merge field. If you want personalized mail merge across recipients, use `create_template` instead. Reserved address zone: a recipient address block is printed over the top ~3 inches of page 1, so the server reserves that space for you automatically. For text/html/markdown/docx, page-1 content is pushed below the block (content may therefore flow onto an additional page); for pdf and image inputs, a blank first page is prepended. As a result the returned page count — and the selected-provider cost behind the resulting quote — can be higher than your source document (e.g. a single-page PDF is stored as 2 pages). You do NOT need to leave the top of your document blank yourself. See the postagent://formats resource for per-format details.
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    Enables AI assistants to search YouTube for videos, channels, and playlists while retrieving detailed analytics and metrics through the YouTube Data API v3. Supports advanced filtering options and provides comprehensive statistics for content discovery and analysis.
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    MIT

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  • Deterministically VERIFY a proposed fix before writing it — runs the same patch-policy + verify_fix + blast-radius gates as `qremediate` (offline, no key, no network). Give the finding, the file's current content, and your proposed FULL corrected content; returns approved:true only if the patch is in-policy, clears the finding, adds no new finding, introduces no network/exec sink, and is bounded in size. This does NOT write the file — you write it, only when approved, and never auto-merge.
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  • Call this for the current Canadian reference interest rates: the Bank of Canada policy (overnight target) rate, the prime rate, and system-average mortgage rates (5-year fixed, variable). Read live from the Bank of Canada (Valet API); each rate carries its own observation date. Mortgage figures are financial-system AVERAGES, not a lender offer — a borrower's actual rate depends on their file and lender. Source: Bank of Canada.
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  • Searches published article content from the provided raumnebenan source with case insensitive text matching. Use this as the first discovery step when the exact slug or id is unknown then call get_article_by_id for full details. Use only this tool output do not use external or inferred data. If required information is missing in this source respond that it is not available in the provided source. Only JSON RPC 2.0 requests are supported.
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  • Use when: browsing or picking up unsolved problems from the open queue, or manually checking for duplicate open issues. Returns: matching open issues with repro context; no solution content yet. Omit query to browse the newest open issues. Do not use when: search_solutions already returned next_action (dedup runs inline on zero-hit searches).
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  • Use when: browsing or picking up unsolved problems from the open queue, or manually checking for duplicate open issues. Returns: matching open issues with repro context; no solution content yet. Omit query to browse the newest open issues. Do not use when: search_solutions already returned next_action (dedup runs inline on zero-hit searches).
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  • Extract a PDF to clean Markdown/LaTeX text via MinerU (great for papers behind no open-access full text — give the user's PDF and get readable text back). Provide pdf_url (downloaded server-side, SSRF-guarded) OR pdf_base64. formula/table toggle math/table reconstruction. Returns {task_id, status, cached, content, chars}: a recently-seen (cached) or small PDF comes back with `content` in one call; a fresh PDF (MinerU is GPU-heavy, minutes) returns status='running' + a task_id — then call extract_pdf_result(task_id) to fetch the text.
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  • Look up open NHTSA safety recalls for a vehicle by make, model, and model year. Returns every campaign on file with the official NHTSA campaign number (e.g. 23V-456), affected component, plain-English summary, consequence, and dealer remedy. Use when the user asks about recalls without providing a VIN. Data source: NHTSA recalls API (api.nhtsa.gov). Free, official US data, updated within days of each campaign opening.
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  • Fetch detailed information about a data asset by its identifier. Resolves the asset, then fetches the requested sections in parallel. Use this after advanced_search or resolve_asset_id to get deeper information about a specific asset. Sections: - overview: asset description, importance, owner, metadata - columns: full column schema with types and descriptions - tests: dbt test coverage (only for assets with a dbt parent) - context_counts: cheap count of linked tickets and Slack threads - tickets: full Jira/Linear ticket content - slack: full Slack thread content (truncated to first 5 messages per thread)
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  • Get the AI-scored insights for a company's recent earnings calls — the management-tone read (a net tone score and a hedging score) and the call's key themes with their computed mention counts and per-theme tone. Newest call first. Verifier-approved — only scored and approved calls appear, so quarters can be missing from the sequence (a gap note flags non-consecutive quarters). Use it to gauge how confident or guarded management sounded and what they talked about most.
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  • Searches FoundRole's published content by semantic similarity and returns the most relevant sources for a job-search question: career-guidance blog articles plus FoundRole site pages that describe the product's features (job tracker, Pro plan and pricing, H1B salary data, AI job search) and industry/sector career landings. Each article carries a title, url, summary, a content excerpt, publication date, and tags; each page carries a title, url, description, and its FAQ entries — enough material to answer the question and link the source. Three optional facets add further result groups: company returns FoundRole's employer profile pages matching that company name; job_title and location return the live job-listing landing pages for that role and place, with open-job counts. The facets describe what the user is asking about — a company mentioned only in passing does not need the company facet. Returns empty groups when nothing is relevant rather than padding with off-topic content. Results are the closest matches to the given question, not an index of the site's full coverage; questions about overall topic coverage are answered by knowledge_topics, which lists the blog's categories and tags with article counts. It does not search job listings; jobs_search covers live roles. Each response includes a system_instruction describing how to present the sources.
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  • Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.
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  • Deterministically VERIFY a proposed fix before writing it — runs the same patch-policy + verify_fix + blast-radius gates as `qremediate` (offline, no key, no network). Give the finding, the file's current content, and your proposed FULL corrected content; returns approved:true only if the patch is in-policy, clears the finding, adds no new finding, introduces no network/exec sink, and is bounded in size. This does NOT write the file — you write it, only when approved, and never auto-merge.
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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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  • 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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