Roboflow MCP Server for CrewAIGive CrewAI instant access to 29 tools to Add Projects To Folder, Auto Label, Cancel Training, and more
Connect your CrewAI agents to Roboflow through Vinkius, pass the Edge URL in the `mcps` parameter and every Roboflow tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
Ask AI about this MCP Server for CrewAI
The Roboflow MCP Server for CrewAI is a standout in the Developer Tools category — giving your AI agent 29 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
from crewai import Agent, Task, Crew
agent = Agent(
role="Roboflow Specialist",
goal="Help users interact with Roboflow effectively",
backstory=(
"You are an expert at leveraging Roboflow tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in Roboflow "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 29 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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
About 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.
When paired with CrewAI, Roboflow becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Roboflow tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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.
The Roboflow MCP Server exposes 29 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 29 Roboflow tools available for CrewAI
When CrewAI connects to Roboflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning computer-vision, dataset-management, model-training, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Add projects to folder on Roboflow
Add projects to a folder (Enterprise)
Auto label on Roboflow
Start an auto-labeling job using foundation models
Cancel training on Roboflow
Cancel an active training job
Create annotation job on Roboflow
Assign a batch of images to a labeler and reviewer
Create folder on Roboflow
Create a project folder (Enterprise)
Create project on Roboflow
Create a new project in a workspace
Delete images on Roboflow
Delete multiple images from a project
Delete project on Roboflow
Delete a project or version (moves to Trash)
Download dataset on Roboflow
Retrieve a download link for a zipped dataset in a specific format
Fork universe project on Roboflow
Fork a public project from Roboflow Universe
Get async task on Roboflow
Track long-running operations like forking or large exports
Get dataset health on Roboflow
Check dataset health (class distribution, missing annotations, etc)
Get image on Roboflow
Get details for a specific image
Get project on Roboflow
Get project details, metadata, and versions
Get root on Roboflow
Verify authentication and retrieve default workspace
Get training results on Roboflow
Retrieve metrics and status for a version training run
Get version on Roboflow
Retrieve metadata for a specific dataset version
List folders on Roboflow
List project folders in a workspace (Enterprise)
List trash on Roboflow
List items in the workspace trash
List workspace projects on Roboflow
List information about a workspace and its projects
Manage image tags on Roboflow
Add, remove, or set tags on an image
Restore trash on Roboflow
Restore an item from the trash
Run inference on Roboflow
Run inference on an image using hosted models
Search project images on Roboflow
Search and filter images within a specific project
Search workspace images on Roboflow
Search and filter images within a workspace
Start training on Roboflow
Start training a model on a dataset version
Stop training on Roboflow
Early stop an active training job
Upload annotation on Roboflow
Attach an annotation file to an existing image
Upload image on Roboflow
Upload an image to a project
Connect Roboflow to CrewAI via MCP
Follow these steps to wire Roboflow into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install CrewAI
pip install crewaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comCustomize the agent
role, goal, and backstory to fit your use caseRun the crew
python crew.py. CrewAI auto-discovers 29 tools from RoboflowWhy Use CrewAI with the Roboflow MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Roboflow through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Roboflow + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Roboflow MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Roboflow for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries Roboflow, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Roboflow tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries Roboflow against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Example Prompts for Roboflow in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Roboflow immediately.
"List all projects in my Roboflow workspace 'industrial-safety'."
"Upload this image URL to the 'Hard Hat Detection' project in workspace 'industrial-safety'."
"Show me the training metrics for version 5 of the 'Forklift Tracking' project."
Troubleshooting Roboflow MCP Server with CrewAI
Common issues when connecting Roboflow to CrewAI through Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Roboflow + CrewAI FAQ
Common questions about integrating Roboflow MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Explore More MCP Servers
View all →
Terraform Cloud (HCP)
42 toolsManage infrastructure lifecycle via Terraform Cloud (HCP) — list organizations, manage workspaces, trigger runs, and inspect state outputs directly from your AI agent.

Woodpecker CI
34 toolsManage your Woodpecker CI instance — control pipelines, monitor agents, and configure repositories directly from your AI agent.

Geetest
6 toolsThe ultimate anti-bot CAPTCHA API — validate users, detect bots, and protect your forms with Geetest v4.

Better Proposals
10 toolsCreate and manage professional proposals via Better Proposals — list proposals, contacts, and templates directly from any AI agent.
