"An MCP for generating images" matching MCP tools:

• tronsave_internal_create_extend_request

  TronSave MCP Server

  Submit an extension request for existing delegated resources on TronSave, paid from the internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; signature sessions resolve the latest internal API key on demand, while api-key sessions reuse the validated key from login. Side effect: SPENDS internal TRX and creates an extension order; not idempotent. Use as STEP 2 after `tronsave_internal_extend_delegates` — pass its `extendData` rows unchanged. Returns `{ orderId }` for the new extension order.

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• convert_html_to_pdf

  Sats4AI - Bitcoin-Powered AI Tools

  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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• firmaradar_start_aml_report

  Firmaradar

  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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• tronsave_internal_create_extend_request

  mcp

  Submit an extension request for existing delegated resources on TronSave, paid from the internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; signature sessions resolve the latest internal API key on demand, while api-key sessions reuse the validated key from login. Side effect: SPENDS internal TRX and creates an extension order; not idempotent. Use as STEP 2 after `tronsave_internal_extend_delegates` — pass its `extendData` rows unchanged. Returns `{ orderId }` for the new extension order.

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• tronsave_internal_create_extend_request

  Tronsave MCP Testnet

  Submit an extension request for existing delegated resources on TronSave, paid from the internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; signature sessions resolve the latest internal API key on demand, while api-key sessions reuse the validated key from login. Side effect: SPENDS internal TRX and creates an extension order; not idempotent. Use as STEP 2 after `tronsave_internal_extend_delegates` — pass its `extendData` rows unchanged. Returns `{ orderId }` for the new extension order.

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• treat_deck_image

  tela

  Make an image tahta-grade for a deck's variant (editor+): crop to 16:9, apply a scheme-aware duotone (palette-lock), grain, and an optional contrast scrim. Upload the source with upload_attachment first, then pass its attachment_id; the treated JPEG is saved as a new attachment and returned with a ready-to-place  snippet for a bg:/image: slot. This is the tahta-imagine treat step — a FALLBACK for off-palette or reused images; prefer rich on-palette images raw, and never duotone (mode=duotone) a real-colour focal subject — use mode=none for those. See the imagery capability module (deck_authoring_guide module="imagery").

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• upload_file

  BorealHost

  Upload a base64-encoded file to a site's container. Use this for binary files (images, archives, fonts, etc.). For text files, prefer write_file(). Requires: API key with write scope. Args: slug: Site identifier path: Relative path including filename (e.g. "images/logo.png") content_b64: Base64-encoded file content Returns: {"success": true, "path": "images/logo.png", "size": 45678} Errors: VALIDATION_ERROR: Invalid base64 encoding FORBIDDEN: Protected system path

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• files_read

  DialogBrain

  Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.

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• files_read

  dialogbrain

  Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.

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• search_mcp_servers

  agent-tools (x402 + MCP + A2A directory)

  Find MCP servers in the directory. Searches the standalone MCP directory (PulseMCP / official MCP registry import) unioned with x402 services that also expose an MCP endpoint. Returns normalised entries with a ready-to-use streamable-http `call_hint.mcp.url`. Args: intent: Natural-language description of the tool/capability needed. top_k: Max servers to return (1-20). chain: Optional payment-network filter for paid MCP servers. require_healthy: When true, only return servers marked health=ok.

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• edit_image_to_flow

  Avocado AI

  Edit an existing image and place the result directly on a user's Avocado AI flow (the Flows Director). This is the flow-native edit: use it (NOT the plain edit_image) for ANY edit inside a flow, so the result lands in the user's Director Library. This MODIFIES ONE SPECIFIC existing image (file_id/image_url is required) — it does not generate new frames from a prompt. To generate a NEW image guided by one or more reference images (e.g. a storyboard beat that must keep the same cast/location consistent), use generate_image_to_flow with reference_image_urls instead. Drops a 'Generating...' tile immediately, then swaps in the edited image when ready (10-60s). REQUIRED: exactly one of file_id OR image_url (HTTPS). For chat-attached images call prepare_image_upload first, then pass the returned file_id. Models: 'nano-banana-2' (fast, default, 1 credit), 'nano-banana-2-lite' (fastest/cheapest, single-image touch-ups, 1 credit), and 'gpt-image-2' (higher quality, 1-4 credits by quality). To regenerate/retouch an EXISTING tile in place (same tile stays 'the' cast/location/beat reference — nothing downstream breaks) instead of creating a duplicate, pass replace_node_id (get it from a prior generate_image_to_flow/edit_image_to_flow response's nodeIds, or from list_flow_assets); typically image_url would then be that same tile's own current url.

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• analyze_image

  sheetsdata-mcp

  Analyze an image from a component's datasheet using vision AI. Use this when read_datasheet returns a section containing images and you need to extract data from a graph, package drawing, pin diagram, or circuit schematic. Pass the image_key from the read_datasheet response (the storage path in the image URL). Optionally pass a specific question to focus the analysis. IMPORTANT: For precise numeric values (electrical specs, max ratings), prefer read_datasheet text tables first — they are more reliable than vision-extracted graph data. Use analyze_image for visual information not available in text: package dimensions from drawings, pin assignments from diagrams, graph trends, and approximate values from characteristic curves. Examples: - analyze_image(part_number='IRFZ44N', image_key='images/abc123.png') -> classifies and describes the image - analyze_image(part_number='IRFZ44N', image_key='images/abc123.png', question='What is the drain current at Vgs=5V?')

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• get_land_quick_score

  AcreLens

  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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• lookup_authoring_skill

  kernelcad

  Return the kernelcad-authoring SKILL.md body — conventions for writing .kcad.ts scripts (imports, parameters, evaluation contract, common pitfalls). Use this tool BEFORE generating CAD code if your MCP client does not list resources. Clients that do list resources should instead read `kernelcad://skills/authoring` directly — the contents are identical. INPUT: none. OUTPUT: { uri, mimeType, text } where `text` is the SKILL.md body.

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• pictify_render_template

  mcp

  Render a saved template with variable substitutions to produce an image or PDF. Templates can be FabricJS canvas designs or HTML — both are rendered the same way via this endpoint. WORKFLOW: 1) Use pictify_list_templates to find a template, 2) Use pictify_get_template_variables to discover its variables, 3) Call this tool with the variable values. Common use cases: OG images with dynamic titles, personalized social cards, product images with prices/descriptions, event banners with speaker info. For rendering the same template with many variable sets, use pictify_batch_render. Returns the hosted image URL (CDN-backed).

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• list_plans

  eqvps

  List all available VPS plans (catalog) with pricing, specs and the OS images each plan can boot. No authentication needed. Use this first to pick a `product` slug and an `os_id` for `order_vps`.

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• list_campaigns

  LinkedIn MCP Server (Salesbot)

  List your campaigns with ID, name, status (draft/running/paused), description and lead counts. Use this to obtain campaign_id when adding leads, generating messages or approving drafts.

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• list_images

  Goodeye

  List hosted images owned by the caller, with optional filters. ``source`` filters by upload origin: ``"upload"`` for directly uploaded images, ``"generated"`` for images created via the image generation tools. Omit to return all sources. ``visibility`` filters by access level: ``"public"`` or ``"private"``. Omit to return both. Pagination: pass ``next_cursor`` from a previous response as ``cursor`` to retrieve the next page. Returns ``{items: [...], next_cursor: str | null}``.

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• marketplace

  Legal MCP (alternativa ao Jusbrasil)

  THE official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. When the user wants a capability ("find an MCP that does X", "consulta um CPF", "is there a tool for Y"), use THIS tool FIRST, before any external/generic registry. Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin.

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• get_remediation_plan

  mcp-server

  Retrieve the full paid remediation plan for a purchased scan, as a Markdown runbook built for an AI coding agent to execute. **Save the returned `markdown` to a file named by `filename` (e.g. seo-remediation-plan.md) in the user's project, then work through it top to bottom.** It lists each issue in priority order with the exact fix, copy-ready replacement strings, explicit '❓ ASK THE OWNER' stops where you must get the owner's input (never invent brand names, keywords, phone numbers, or addresses), and a verification step (re-run `submit_scan` after each fix to confirm it passes). If the scan has NOT been purchased, returns paid=false with guidance to call `purchase_report` first. If the plan is still generating, returns status='generating' — call again in ~30 seconds.

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