"A server for creating UI components from PNG files" matching MCP tools:

• upload_media

  SendIt

  FOR CLAUDE DESKTOP ONLY (with filesystem access). For Claude.ai/web: Use create_upload_session instead - it provides a browser upload link. Upload local media to cloud storage, returning a public HTTPS URL. WHEN TO USE: • Instagram, LinkedIn, Threads, X: REQUIRED for local files before calling publish_content • TikTok: NOT NEEDED - pass local path directly to publish_content SUPPORTED FORMATS: • Images: jpg, png, gif, webp (max 10MB) • Videos: mp4, mov, webm (max 100MB) Returns { url: 'https://...' } for use in publish_content mediaUrl parameter.

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• read_file

  BorealHost

  Read the contents of a file from a site's container. Max file size: 512KB. Binary files are rejected — use the site's file manager or SSH for binary files. Requires: API key with read scope. Args: slug: Site identifier path: Relative path to the file Returns: {"path": "wp-config.php", "content": "<?php ...", "size": 1234, "encoding": "utf-8"} Errors: NOT_FOUND: File doesn't exist VALIDATION_ERROR: File is binary or exceeds 512KB

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• sigil_score_entity

  TunnelMind Data API

  Returns the pre-computed 0.0–1.0 trust score for one entity, its component breakdown, and the 14-day trend. Scores are refreshed daily by a database job — this endpoint never recomputes from raw data, so it is fast and deterministic. `entity_id` is `{entity_type}:{key}` — e.g. `publisher:nytimes.com` or `ssp:pubmatic.com`. Entity types: `publisher`, `ssp`, `dsp`, `app_bundle` (publishers and SSPs are scored today). v1 evaluates structural components only (`ads_txt_health`, `supply_chain_directness`, `historical_stability` for publishers; `supply_reach`, `directness` for SSPs). The `not_evaluated` list names spec components without an enrichment path yet. Optional `weights` query param (URL-encoded JSON) re-weights the stored components for this call.

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• get_graph_template_schemas

  RationalBloks

  Get pre-built graph template schemas for common use cases. ⭐ USE THIS FIRST when creating a new graph project! Templates show the CORRECT graph schema format with: proper node definitions (description, flat_labels, schema with flat field definitions), relationship configurations (from, to, cardinality, data_schema), and hierarchical entity nesting. Available templates: Social Network (users, posts, follows), Knowledge Graph (topics, articles, authors), Product Catalog (products, categories, suppliers). You can use these templates directly with create_graph_project or modify them for your needs. TIP: Study these templates to understand the correct graph schema format before creating custom schemas.

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• vf_health

  VoiceFlip

  Returns VoiceFlip MCP server health and version metadata. No authentication required. Use this first to verify the server is reachable from your MCP client.

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• get_api_key_instructions

  Kamy

  Return step-by-step instructions for creating a Kamy API key in the dashboard. Does not open the browser.

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• list_components

  HTML Email Playbook

  List all reusable email components in the playbook with their metadata: name, subcategory (layout/media/interactive/text), description, whether they require Outlook VML, and whether they are responsive. Use this first to discover what components exist before calling get_component.

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• list_docs

  Pine Script

  List all available Pine Script v6 documentation files with descriptions. Returns files organised by category with descriptions. For small files use get_doc(path). For large files (ta.md, strategy.md, collections.md, drawing.md, general.md) use list_sections(path) then get_section(path, header).

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• roamzy_get_esim

  mcp-server

  Get a specific eSIM by id, including msisdn, status, balance, and the activation block (qr_payload + lpa_url). ⚠️ QR RENDERING: This tool does NOT return a ready-to-display image. Instead, qr_payload contains the LPA URI string. YOU must generate the QR PNG yourself using your code-execution tools (Python qrcode library, JS qrcode npm package, etc.) and offer the resulting PNG as a downloadable file to the user. DO NOT use external QR-generation services — they show ugly UI dialogs in Claude Desktop and require external trust. Local generation gives the user a real downloadable PNG they can save and scan. ALWAYS caption the QR (once generated) with «Ваш номер eSIM: <msisdn>» / «Your eSIM number: <msisdn>». The lpa_url field is ONLY for users installing on the SAME phone where they're reading the chat (camera can't scan own screen) — surface it as a text fallback for that case, prefixed «LPA URI (manual entry):». Do NOT show internal IDs (id, display_id, iccid) to the user. ⚠️ ANON-MODE RECOVERY REMINDER: If this is an anonymous Roamzy session (no ROAMZY_API_TOKEN env was set), after presenting the QR you MUST also re-surface the claim_url from the original roamzy_create_order response with this framing: «❗ Не забудь сохранить ссылку восстановления — без неё ты не вернёшься к этой eSIM из другого Claude-чата». If the user has already closed-and-reopened the chat and lost the claim_url, instruct them to contact Roamzy support (call roamzy_support tool) with their MSISDN + NowPayments transaction hash for manual recovery — operator can mint a fresh claim_url. If the user follows up with «how do I contact support» or «refund» — call roamzy_support, not web search.

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• xmp4_grep

  xmp4 — Semantic code knowledge for your stack

  Server-side regex text search over indexed project source files. Free tier: requires file_path (single file). Premium tier (XMP4_PREMIUM_GREP_WALK=true): allows file_glob multi-file walk. Prefer xmp4_tests_for/xmp4_usages for SCIP symbols — grep is for text not indexed (comments, literals, config keys).

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• sigil_score_weights

  TunnelMind Data API

  Returns the active, versioned default weights used to combine an entity's trust-score components, plus the list of spec components that are not yet evaluated. Pass a custom `weights` object to `sigil_score_batch` to re-weight without changing the defaults.

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• get_install_instructions

  petal-components-mcp

  Get the canonical steps for installing petal_components in a Phoenix project. Call this when the user asks to install petal_components, when you are setting up a new Phoenix project that needs UI components, or when verifying an existing installation. Returns step-by-step instructions covering mix.exs, mix deps.get, Tailwind v4 CSS config, and the web module import. Steps are idempotent - safe to follow on a project that is partially configured.

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• ateam_upload_connector

  ateam-mcp

  Upload connector code to Core and restart — WITHOUT redeploying skills. Use this to update connector source code (server.js, UI assets, plugins) quickly. Set github=true to pull files from the solution's GitHub repo, or pass files directly. Much faster than ateam_build_and_run for connector-only changes.

  Connector

• execute_sql_readonly

  Google Big Query

  Run a read-only SQL query in the project and return the result. Prefer this tool over `execute_sql` if possible. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) Queries executed using the `execute_sql_readonly` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `project_id` field.

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• upload_image

  Real Real Genuine

  Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...

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• get_doc

  Pine Script

  Read a specific Pine Script v6 documentation file. For large files (ta.md, strategy.md, collections.md, drawing.md, general.md) prefer list_sections() + get_section() to avoid loading 1000-2800 line files into context.

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• code_get_files

  searchcode

  Get contents of multiple files from a remote public git repository in a single call. Reduces round-trips when you need to read several related files. Max 10 files per batch, 5000 total lines budget across all files. Each file supports optional line ranges. Failed files return per-file errors without blocking other files.

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• upload_image

  Real Real Genuine

  Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...

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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_attachment

  gmail

  Download an email attachment by its ID. Use after get_email to fetch the actual attachment content. Pass the filename and mimeType from get_email's attachment metadata. Text files (txt, csv, json, html, xml, md) are returned as decoded text. Images (png, jpg, gif, webp) are returned as viewable image content. Other files are returned as base64-encoded data. Attachments over 10MB are rejected.

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