"A platform for downloading images from Unsplash using specified keywords" matching MCP tools:

• get_creator

  Influship Influencer Marketing MCP

  Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.

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• dispatch_social_listening_researcher_async

  Heista

  Dispatch to the SOCIAL LISTENING RESEARCHER — multi-platform community-signal interpretation. Use for: "what are practitioners saying about X across platforms / what jargon is emerging in field Y / what is the cross-platform discourse around brand/topic Z". Treats T3 community sources as primary data, distinguishes cross-platform patterns from single-platform noise. ≥3 platforms sampled per brief. Returns: Signal map (Signal / Platforms / Volume / Sentiment + recency) + Per-platform evidence trail + Cross-platform vs single-platform classification + Confidence flag + Sources. NOT for: single-source thematic work (use dispatch_qualitative_researcher) / numerical sentiment effect sizes (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

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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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• wait_for_task

  Agent Router

  Wait for a platform agent task to complete and return its result. Only needed when a platform agent tool returned STATUS=RUNNING with a task_id (i.e. the task was still running after the initial 50s inline wait). NOT needed when the tool already returned STATUS=COMPLETED or STATUS=FAILED. NOT needed for a2a_call_agent — that always returns directly. Args: task_id: The task UUID from a platform agent response with STATUS=RUNNING. max_wait_seconds: Max seconds to wait (default 45, max 300).

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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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• restore_version

  WebSlop

  DESTRUCTIVE: Restore an app to a previous version using git reset --hard. This permanently overwrites all current files with the state from the specified commit — any changes made after that commit will be lost and CANNOT be recovered. You MUST confirm with the user before calling this tool. Use list_versions to show the user available versions first.

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• sti_get_platforms

  Stimulsoft Documentation MCP Server

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

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• videos_generate

  dialogbrain

  Generate a short video (5-10s) from a text prompt using BytePlus Seedance. Optionally accepts up to 12 image file IDs from the user's attached files (visible in the [ATTACHMENTS] block) as `reference_file_ids` for style and composition. Returns immediately with a job_id; the video is delivered back via continuation when the job completes (~30-90s for fast model, ~2-5min for pro). Reference images are temporarily re-hosted on a third-party CDN (imgbb) for the duration of generation and deleted on completion — don't submit confidential references. Gated behind a workspace opt-in flag.

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• get_account_metrics

  SocialGPT

  Get per-platform engagement (views / likes / comments / shares) as a time series over the trailing window_days (default 28, up to 365). Omit account_id to aggregate across all connected accounts, or pass one from list_accounts; optionally filter to a single platform. post_limit (≤100) fixes how many recent posts form the baseline. granularity buckets the series server-side ('daily' default, 'weekly', or 'raw' for every scrape). Read `series` (a clean per-platform list of typed points) — `metrics` is the legacy column/data matrix kept for back-compat. NB: follower counts here are latest-only; for audience growth over time use get_follower_history.

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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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• downloadEmailAttachments

  email

  Download all attachments for an inbound email as a gzip-compressed tar archive. Returns the archive as a base64-encoded string along with the attachment count and SHA-256 digest. Prefer getEmail first to check the attachment manifest before downloading.

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• pause_email_account

  mailopoly

  Pause (turn off) a connected account: stop downloading new mail while KEEPING everything already brought in. `account` is the connected email address. Reversible with resume_email_account. Confirm with the user before pausing — it stops their email from updating.

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• erase

  cnvs.app

  Delete a single item by id. `kind` MUST match the item type: 'text' for text nodes, 'line' for freehand strokes, 'image' for images — the wrong kind silently targets the wrong table and is a common mistake. Get the id + type from `get_board` (texts[], lines[], images[]). There is no bulk/erase-all tool: loop if you need to delete multiple items.

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• get_video_info

  TubePull

  Fetch metadata about a video or audio track WITHOUT downloading it. Works on every platform download_video supports: YouTube, TikTok, Vimeo, Dailymotion, Twitter/X, SoundCloud, Bandcamp, Mixcloud, Twitch, and Streamable. Returns title, uploader/channel name, duration, view count (when available), upload date, thumbnail URL, description, available video qualities, and (for YouTube) the license type. Use this tool when the user says things like: - "what is this video about" / "summarize this video" - "how long is this track" / "when was this uploaded" - "who made this" / "what channel/artist is this from" - "is this Creative Commons" / "can I reuse this" / "what is the license" - "what qualities are available for this video" Do NOT use this tool when: - The user wants to download, save, rip, extract, or convert the video/audio — use download_video for that. Free to call — does not count against the user's download quota. Call this before download_video when you need to confirm the video exists, pick the right quality, or check licensing before downloading.

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• messages_send

  dialogbrain

  Send a message to a thread, channel, or contact. Supports Telegram, Email, LinkedIn, and other connected channels. For LinkedIn posts (comment_thread kind), this posts a comment on the post. Can automatically resolve recipients and channels when not specified. Can send files/images/documents as attachments — pass `attachments=[file_id, ...]` with integer file IDs obtained from collections.list_files, search.files, or files.search. `text` is optional when attachments are provided.

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• get_creator

  Influship

  Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.

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• list_chapters

  bookstore4agents

  List the chapters (table of contents) of a purchased book without downloading the full text. Pass the download_url from the purchase response. Returns each chapter's index, title, and length. Use read_chapter to fetch a single chapter at a time instead of pulling the whole book at once.

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• create_task

  renthuman

  Create a task for human executors. Cost = reward × max_executors × 1.2 (20% platform fee), charged from your balance into escrow. Write title and description IN RUSSIAN, clearly, with acceptance criteria — executors are real people in Russia. Returns task_id.

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• aetherwave_upscale_image

  AetherWave Studio

  Upscales a source image using Topaz's high-fidelity upscaler. Pass a public `imageUrl` and an `upscaleFactor`. Credit cost depends on the source resolution × factor; small images cost less than large ones at the same factor. Returns the upscaled image URL.

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• 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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