How to Use the Image Router MCP in CrewAI

Q: How do CrewAI agents use Image Router to select the right model?

The crew's coordinator agent calls listmodelsbycategory to find models that match the required medium. The MCP Server then automatically handles the backend routing when the agent calls generateimage.

Q: How does Image Router handle API downtime during a CrewAI run?

The server uses checkimagerouterstatus to verify connection health. If a backend service is unresponsive, your monitoring agent can catch the status and redirect the task to another active model.

Q: Can my agents fetch details about a specific model?

Yes, your agents can call getmodel to retrieve performance metrics and resolution capabilities. This allows the crew to make informed decisions about which model to use for high-resolution tasks.

Equip your CrewAI agent teams with this MCP Server to automate image routing and generation.

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Create your Vinkius account to connect Image Router to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Image Router with CrewAI

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Perplexity

Specialized image tasks for CrewAI agent teams

The `generate_image` tool gives your designer agents the ability to create high-quality assets autonomously. This MCP Server lets a researcher agent gather concepts, write a prompt, and hand it to the designer agent to execute. When revisions are needed, a critic agent can call `edit_image` to modify specific parts of the asset. This collaborative loop runs without human intervention, using the best model for each specific edit.

Advanced generation control for autonomous crews

The `generate_image_advanced` tool provides your agents with deep control over dimensions, aspect ratios, and negative prompts. Your lead agent can dynamically adjust these settings based on the requirements of the task. If the crew needs to explore different visual directions, `generate_variation` creates alternative options from a single base image. This allows your agents to present multiple creative routes to the user.

Model selection and status monitoring

The `list_models` tool allows your manager agent to inspect all available generation engines before assigning a task. The agent can match the budget and quality requirements to the right model on the fly. While the generation runs, the monitoring agent uses `get_generation_status` to track progress. This keeps the entire crew coordinated, ensuring downstream agents only start their tasks when the image is ready.

Setup guide

Set up Image Router MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Image Router tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Image Router Analyst",
    goal="Access and analyze Image Router data via MCP.",
    backstory="Expert analyst with direct Image Router access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Image Router transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Image Router Analyst",
        goal="Access and analyze Image Router data via MCP.",
        backstory="Expert analyst with direct Image Router access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Image Router transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Image Router. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Image Router MCP in CrewAI

The crew's coordinator agent calls `list_models_by_category` to find models that match the required medium. The MCP Server then automatically handles the backend routing when the agent calls `generate_image`.

Yes, you can use CrewAI's tool filtering to expose only specific tools like `upscale_image` or `list_styles` to individual agents. This keeps your researcher agents focused on metadata and your designer agents focused on generation through the MCP Server.

The server uses `check_imagerouter_status` to verify connection health. If a backend service is unresponsive, your monitoring agent can catch the status and redirect the task to another active model.

Yes, your agents can call `get_model` to retrieve performance metrics and resolution capabilities. This allows the crew to make informed decisions about which model to use for high-resolution tasks.

All image files, prompt strings, and style parameters are handled via secure, ephemeral connections. The server never caches or logs your visual assets, ensuring your crew's intellectual property remains private.

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