Compatible with every major AI agent and IDE
What is the Roboflow MCP Server?
Connect Roboflow to your AI agent to streamline your computer vision pipeline. From dataset management to model training and inference, handle your entire CV lifecycle through natural language.
What you can do
- Workspace & Project Management — List projects, create new ones, or fork from Roboflow Universe to jumpstart your development.
- Dataset Operations — Upload images (via URL or Base64), manage versions, and download datasets in various formats like COCO or YOLO.
- Model Training — Start training runs, monitor results, and retrieve precise performance metrics (mAP, precision, recall) for any version.
- Image Search — Search and filter images within your workspace to audit your data and improve model accuracy.
- Inference & Results — Run inference on images and retrieve results to verify model behavior in real-time.
How it works
- Subscribe to this server
- Enter your Roboflow Private API Key
- Start building and managing vision models from Claude, Cursor, or any MCP-compatible client
Who is this for?
- ML Engineers — monitor training progress and dataset health without leaving the terminal or IDE.
- Data Scientists — quickly query dataset versions and export data for custom training scripts.
- Product Teams — audit model performance and visualize inference results through simple conversation.
Built-in capabilities (29)
Add projects to a folder (Enterprise)
Start an auto-labeling job using foundation models
Cancel an active training job
Assign a batch of images to a labeler and reviewer
Create a project folder (Enterprise)
Create a new project in a workspace
Delete multiple images from a project
Delete a project or version (moves to Trash)
Retrieve a download link for a zipped dataset in a specific format
Fork a public project from Roboflow Universe
Track long-running operations like forking or large exports
Check dataset health (class distribution, missing annotations, etc)
Get details for a specific image
Get project details, metadata, and versions
Verify authentication and retrieve default workspace
Retrieve metrics and status for a version training run
Retrieve metadata for a specific dataset version
List project folders in a workspace (Enterprise)
List items in the workspace trash
List information about a workspace and its projects
Add, remove, or set tags on an image
Restore an item from the trash
Run inference on an image using hosted models
Search and filter images within a specific project
Search and filter images within a workspace
Start training a model on a dataset version
Early stop an active training job
Attach an annotation file to an existing image
Upload an image to a project
Why Google ADK?
Google ADK natively supports Roboflow as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 29 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
- —
Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
- —
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Roboflow
- —
Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
- —
Seamless integration with Google Cloud services means you can combine Roboflow tools with BigQuery, Vertex AI, and Cloud Functions
Roboflow in Google ADK
Roboflow and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Roboflow to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Roboflow in Google ADK
The Roboflow MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 29 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Roboflow for Google ADK
Every tool call from Google ADK to the Roboflow MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I verify if my Roboflow API key is correctly configured?
You can use the get_root tool. It will attempt to authenticate with your key and return the default workspace details if successful.
Can I get the training performance metrics for a specific model version?
Yes! Use the get_training_results tool by providing the workspace, project, and version ID. It returns mAP, precision, recall, and other training metrics.
Is it possible to export my dataset to a specific format like YOLOv5?
Absolutely. Use the download_dataset tool and specify the format parameter (e.g., 'yolov5pytorch') to receive a download link for your zipped dataset.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk
Explore More MCP Servers
View all →
Dubsado
12 toolsRun your creative business with proposal templates, contract signing, invoicing, and client scheduling in one seamless flow.

LlamaIndex (AI Data Framework & RAG)
6 toolsQuery and manage RAG pipelines via LlamaIndex — execute natural language searches, audit indexed files, and monitor data pipelines.

AdRoll
5 toolsE-commerce marketing and retargeting — manage campaigns, ads, and performance via AI.

Gitee
10 toolsCollaborative code hosting and development platform — manage repositories, issues, and pull requests via AI.
