# Google Cloud Vision — how to use (mcp.ai)

Connect your Google Cloud Vision account and use 29 tools for artificial intelligence straight from your AI agent. Connect with your own API key. Google Cloud Vision API enables developers to integrate vision detection features into applications, including image labeling, face and landmark detection, optical character recognition (OCR), and explicit content tagging.

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_google_cloud_vision?ms=1787293380000`
Add it as a custom/remote MCP connector in your client (Claude, Cursor, VS Code…), then authenticate when prompted. Once connected, ask the agent to use the server's tools (e.g. `google_cloud_vision_annotate_files`).

## Option B — via direct REST API
Base URL: `https://api.mcp.ai/api/google_cloud_vision`
Auth: `Authorization: Bearer sk_live_…` — create a workspace API key at https://mcp.ai/settings/api-keys
Discover endpoints: `GET https://api.mcp.ai/api/google_cloud_vision/_endpoints`

### Endpoints
- `POST https://api.mcp.ai/api/google_cloud_vision/annotate/files` — Tool to perform image detection and annotation for batch files in Google Cloud Vision. Supports PDF, TIFF, and GIF files. Extracts up to 5 frames (GIF) or pages (PDF/TIFF) from each file and performs 
  - body: { parent: string, requests: object[] }
- `POST https://api.mcp.ai/api/google_cloud_vision/annotate/files/async/batch` — Tool to run asynchronous image detection and annotation for a list of generic files (PDF, TIFF, GIF). Use when processing multi-page documents that may contain multiple images per page. Results are wr
  - body: { parent?: string, requests: object[] }
- `POST https://api.mcp.ai/api/google_cloud_vision/annotate/images` — Run image detection and annotation for a batch of images using Google Cloud Vision API. Performs various types of image analysis including face detection, landmark detection, logo detection, label det
  - body: { parent?: string, requests: object[] }
- `POST https://api.mcp.ai/api/google_cloud_vision/annotate/images/async/batch` — Tool to run asynchronous image detection and annotation for a batch of images. Use when processing multiple images or large images that require longer processing time. Results are written to Google Cl
  - body: { parent: string, requests: object[], outputConfig: object }
- `POST https://api.mcp.ai/api/google_cloud_vision/annotate/location/images` — Tool to run image detection and annotation for a batch of images scoped to a specific project and location. Performs various types of image analysis including label detection, face detection, landmark
  - body: { parent: string, requests: object[] }
- `POST https://api.mcp.ai/api/google_cloud_vision/create/product` — Creates a new Product resource in Google Cloud Vision Product Search. A Product represents a physical item that can be visually searched using reference images. After creating a product, you can add r
  - body: { parent: string, productId?: string, description?: string, displayName: string, productLabels?: object[], productCategory: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/create/product/set` — Creates a new ProductSet resource in Google Cloud Vision Product Search. A ProductSet is a container for grouping related products together for visual search. After creating a product set, you can add
  - body: { parent: string, displayName: string, productSetId?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/create/reference/image` — Tool to create a ReferenceImage under a product. Use when adding a new image to a product for detection.
  - body: { uri: string, parent: string, boundingPolys?: object[], referenceImageId?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/delete/product` — Permanently deletes a Product and its associated reference images from Google Cloud Vision API. This is a destructive operation that cannot be undone. The product metadata and all images are deleted i
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/get/product` — Tool to get information associated with a Product. Use when you have the product resource name and need its details.
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/get/product/set` — Tool to get a ProductSet. Use when you need metadata details of an existing ProductSet by its full resource name. Use after obtaining the resource name.
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/import/product/sets` — Asynchronously imports product sets and reference images from a CSV file stored in Google Cloud Storage. This bulk import operation creates ProductSets, Products, and ReferenceImages from a properly f
  - body: { parent: string, inputConfig: object }
- `POST https://api.mcp.ai/api/google_cloud_vision/list/index/endpoints` — Lists IndexEndpoints in Vertex AI Vision for a given project and location. IndexEndpoints are deployed instances of image indexes used for visual search and retrieval in Vision AI's media warehouse. U
  - body: { filter?: string, parent: string, pageSize?: integer, pageToken?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/list/locations` — Tool to list available Vision AI service locations for a project. Use when you need to discover supported regions before making region-specific API calls.
  - body: { name: string, filter?: string, pageSize?: integer, pageToken?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/list/operations` — Tool to list operations that match the specified filter. Use when you need to retrieve all operations under a specific project and location.
  - body: { name: string, filter?: string, pageSize?: integer, pageToken?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/purge/products` — Tool to asynchronously delete products in a ProductSet or orphan products. Use when you need to clean up products at scale; ensure `force` is true to execute.
  - body: { force: boolean, parent: string, deleteOrphanProducts?: boolean, productSetPurgeConfig?: object }
- `POST https://api.mcp.ai/api/google_cloud_vision/update/product` — Tool to update a Product's mutable fields: displayName, description, and productLabels. Use after confirming the product resource name.
  - body: { name: string, updateMask?: string, description?: string, displayName?: string, productLabels?: object[] }
- `POST https://api.mcp.ai/api/google_cloud_vision/update/product/set` — Tool to update a ProductSet resource. Use when you need to modify the displayName of an existing ProductSet.
  - body: { name: string, updateMask?: string, displayName: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/add/product/to/product/set` — Add a Product to a ProductSet in Google Cloud Vision Product Search. This action associates a Product with a ProductSet, enabling the product to be included in product search queries against that set.
  - body: { name: string, product: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/cancel/operation` — Starts asynchronous cancellation of a long-running Vision API operation. Returns an empty response on successful cancellation request. Note that the server makes a best effort to cancel the operation,
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/delete/operation` — Tool to delete a long-running Vision API operation. Use after confirming the operation name.
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/delete/product/set` — Tool to permanently delete a ProductSet. Use after confirming the ProductSet's resource name.
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/delete/reference/image` — Permanently removes a reference image from a product in Google Cloud Vision Product Search. This action deletes the reference image association from the specified product. The image will be marked for
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/get/operation` — Retrieves the latest state of a long-running Vision API operation. Use this to poll the status of asynchronous operations like importProductSets or purgeProducts. The operation name is returned when y
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/get/reference/image` — Tool to get information associated with a ReferenceImage. Use when you have the full resource name and need its metadata.
  - body: { name: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/list/products/in/product/set` — Tool to list Products in a specified ProductSet. Use when you need to retrieve Products associated with a ProductSet after confirming it exists, with optional pagination.
  - body: { name: string, pageSize?: integer, pageToken?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/list/projects` — List Google Cloud projects accessible to the authenticated user via Cloud Resource Manager API. This action queries the Cloud Resource Manager API (not Vision API directly) to enumerate projects. It r
  - body: { filter?: string, pageSize?: integer, pageToken?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/list/reference/images` — Tool to list reference images for a product. Use when you need to retrieve stored reference images under a specified product resource name, with optional pagination.
  - body: { parent: string, pageSize?: integer, pageToken?: string }
- `POST https://api.mcp.ai/api/google_cloud_vision/vision/remove/product/from/product/set` — Removes a Product from a specified ProductSet in Google Cloud Vision API. This operation unlinks a product from a product set but does not delete either resource. Both the product and product set must
  - body: { name: string, product: string }

## Example prompts
- "What can I do in Google Cloud Vision?"
- "Show me a summary of my Google Cloud Vision account"

## More
- Page: https://mcp.ai/google_cloud_vision
- Agent spec (llms.txt): https://mcp.ai/google_cloud_vision/llms.txt
- Postman collection: https://mcp.ai/google_cloud_vision/postman.json