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470,086 tools. Updated 2026-08-21 11:50

"Tools or software for generating diagrams" matching MCP tools:

  • Quick pre-publish compliance gate before generating a listing. Fast, free scan for obvious red-line words and category risks. Returns a shallow pass/fail-style result, not a full audit. Use this as a cheap pre-check right before generation. Do NOT use it for a complete risk report - use compliance_scan for the deep knowledge-base audit. Read-only; requires an API key; no credits deducted. Args: text: listing copy (required). lang: zh or en (default en). category: optional category hint, e.g. electronics or apparel.
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  • Start generating an AML risk report ASYNCHRONOUSLY for a Norwegian company. Returns immediately with a report_id and status 'pending' — the report is built in the background. Poll `get_aml_report` with the report_id until status is 'done' (then read score/level/factors) or 'failed'. Use this instead of `get_aml_score` for large/complex ownership structures that may otherwise time out, or to start many screenings in parallel. Generates an auditable report stored for 60 months per Hvitvaskingsloven §35.
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  • Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.
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  • Check an async report job by report_id (from report_request or report_list). Returns its status: _PENDING_ or _IN_PROGRESS_ (still generating — wait a bit and check again) or _DONE_. When _DONE_, result_url is a download link for the result ZIP; hand it to the user. Links are time-limited — if one has expired, run report_status again for a fresh link. The server never downloads the file itself.
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  • Convert HTML or Markdown to a pixel-perfect PDF. Returns JSON: { url } — a temporary download URL (valid ~1 hour). Great for generating invoices, reports, receipts, or formatted documents programmatically. Supports full HTML/CSS including tables, images (base64 or URL), and inline styles. For Markdown input, set format='markdown'. 50 sats per conversion. Use convert_file instead for converting existing files between formats (e.g., DOCX→PDF). Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='convert_html_to_pdf'.
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  • WHEN: you need the COMPLETE bidirectional relation graph for an object in ONE call. Triggers: 'relations of', 'FK of', 'what tables link to', 'quelles tables liées à', 'avant de générer du code', 'before generating code', 'foreign keys', 'delete actions', 'who references', 'qui référence', 'graph de relations'. Returns ALL outgoing edges (FK relations, DeleteActions, DataSources, Extensions, Security...) AND all incoming back-references (forms, entities, CoC classes, privileges... that reference it). Backed by the pre-computed relation index -- O(1) lookup, no vector scan. Much faster and more complete than find_related_objects for known object names. ALWAYS call this before generating code that touches multiple objects or requires join logic. Use find_related_objects when the relation index is not yet built (fallback to vector scan).
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables generating cloud architecture diagrams, flowcharts, sequence diagrams, and more using three rendering engines: mingrammer/diagrams, Mermaid, and PlantUML.
    3
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables automatic generation of UML class diagrams and entity-relationship diagrams from natural language descriptions or structured JSON data. It integrates with MCP agents to create visual representations of code structures and system designs without manual Mermaid coding.
    12
    1
    MIT

Matching MCP Connectors

  • Generate cloud architecture diagrams, flowcharts, and sequence diagrams.

  • Decision Layer for AI Agents — 58+ tools, Advisor, MCP. Free key: POST /v1/register {}.

  • Use this when the user asks whether a specific AI tool is alive, dead, shut down, still maintained, safe to adopt, or trustworthy — or asks for its current health, viability, or verification status. Returns a verified verdict (healthy / monitor / at-risk / shut down / delisted) with evidence: link-health probe results, a 5-signal viability assessment, real-user market sentiment, pricing reality, and verified-alive alternatives. Data comes from the RightAIChoice verification engine: 8,000+ AI tools with every vendor link re-probed on a rolling weekly cycle. Every answer states when it was last verified. Not for: tools outside the AI/software space, historical company research, or legal/financial advice. An "unknown" result means the tool is not in the catalog — it is not evidence the tool is dead.
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  • Search the Axint Registry for already-published packages that match a natural-language query. Use this BEFORE calling axint.feature or axint.compile so the agent can install an existing package instead of regenerating Swift the community has already shipped. Use: use before generating code to find reusable packages; not for validating local Swift. Inputs: query drives ranking; kind and platform narrow results without changing the registry source. Effects: read-only local registry search using AXINT_REGISTRY_PATH or sibling checkout; no network by default.
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  • Render a mingrammer/diagrams Python snippet to PNG and return the image. The code must be a complete Python script using `from diagrams import ...` imports and a `with Diagram(...)` context manager block. Use search_nodes to verify node names and get correct import paths before writing code. Read the diagrams://reference/diagram, diagrams://reference/edge, and diagrams://reference/cluster resources for constructor options and usage examples. Args: code: Full Python code using the diagrams library. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.
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  • Look up a MITRE ATT&CK threat group (intrusion set) or software entry by name or ID for authorized penetration testing and threat intelligence. Returns the group or software record: ATT&CK ID, display name, known aliases, type (group vs. software), description, and the techniques it uses with procedure-level context from public ATT&CK reporting. Accepts exact ATT&CK IDs (G0007 for threat groups, S0002 for software) or keyword/name search (e.g., "APT28", "Mimikatz", "Lazarus Group"). Equally useful for defenders building detection coverage around specific adversary tradecraft.
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  • Queries CNAE (National Classification of Economic Activities) from IBGE. CNAE is the official classification for economic activities in Brazil. Hierarchical structure: - Section (letter A-U): 21 main categories - Division (2 digits): 87 divisions - Group (3 digits): 285 groups - Class (4-5 digits): 673 classes - Subclass (7 digits): 1,332 subclasses Features: - Search by CNAE code - Search by activity description - List by hierarchical level - Show complete hierarchy Examples: - Search software: busca="software" - Specific code: codigo="6201-5/01" - View section: codigo="J" - List divisions: nivel="divisoes" Behavior: read-only and idempotent — a live GET against the public IBGE CNAE API. Returns Markdown.
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  • Free preview of breaking changes / new releases for a software dependency. Pass an npm/PyPI `package` (resolved and fetched live if not already tracked) or a GitHub `repo` (owner/repo). Returns up to 5 recent changes plus the package's current version. Full history, significance filtering, and the LLM brief are paid via x402.
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  • Get a fast suitability score (0-100) for a US property without generating a full report. Call this when the user wants a quick go/no-go assessment or an initial screening before committing to a full analysis. Returns a single score with confidence level and one-sentence rationale. Consumes a partial (0.25) analysis credit from your AcreLens account.
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  • Start a batch render job to generate multiple images from a single template — from inline variable sets, or from a hosted CSV where every row becomes a render. Each variable set produces a separate image. Supports up to 100 items per batch (plan-dependent). Common use cases: generating personalized social cards for all team members, product images for an entire catalog, event badges for all attendees, certificate images for course graduates, or marketing assets with localized content. WORKFLOW: 1) Use pictify_get_template_variables to discover variables, 2) Call this tool with an array of variable sets, 3) Use pictify_get_batch_results to poll for completion and get result URLs. The job runs asynchronously — this tool returns immediately with a batchId (HTTP 202). For generating a single multi-page PDF instead, use pictify_render_multi_page_pdf.
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  • List pre-configured group-conversation templates. Templates are shapes for common multi-agent setups: software team, research pod, content team. Each has a slug, default title + description, suggested role labels, and an optional starter message that gets pinned at creation. Use ``colony_create_group_from_template`` with the slug to create.
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  • Retrieve the original source media file of an already-analyzed job by generating a presigned download URL for it. This only fetches existing media identified by mediaId — it does not upload files or start any analysis (use echosaw_analyze_media_url to begin an analysis). The URL is valid for 1 hour.
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  • Create an empty diagram and return its diagram_id, so you can build it yourself with the canvas_* tools. No AI generation runs and no credit is spent — you draw it. Use this when you want control over the result, or already know the architecture from the conversation. Use create_diagram instead when you want Datadef's model to design the whole thing from a prompt. Call get_design_guide first — it is the standard Datadef's own generator follows, and building without it produces diagrams this tool exists to avoid.
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  • Get full detail for a Tuki solution: description, who it is for, capabilities, status and contact / CTA. Use after `list_solutions` or when the user asks about a specific Tuki product (WhatsApp Booking OS, boutique ticketing, rental inventory software, event post-sale, tailor-made tourism software).
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  • Returns ALL FK/DeleteAction/DataSource relations (outgoing) AND back-references (incoming). Call BEFORE generating multi-object code to understand the full dependency graph. When the relation index is loaded, delegates to get_relation_graph (O(1)) internally — do NOT call both tools for the same object.
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