How to Use the Viesus MCP in CrewAI

Run Autonomous, Multi-Agent Image Processing Pipelines with CrewAI and Viesus.

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Connect Viesus MCP to CrewAI

Create your Vinkius account to connect Viesus 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 Viesus with CrewAI

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Claude

Perplexity

Specialized Agent Collaboration

You can build a team. Agent A uploads the image using `upload_image_to_viesus`. Agent B checks the required format via `list_supported_file_formats`, and then Agent C kicks off enhancement with `enhance_image_ai`. This role-based specialization makes sure each step of the pipeline is handled by the right tool call.

Monitoring and Escalation

A monitor agent needs to watch for trouble. If a job status check via `get_enhancement_job_status` stalls, the monitor agent can automatically escalate the issue by listing recent failures using `list_processing_history`. This creates a self-correcting system that doesn't require human intervention.

Structured Data Gathering

Before action, your crew needs data. Have an agent pull all available configuration options by listing `list_enhancement_presets`. Another agent can then retrieve specific details using `get_image_metadata` to make a final decision. This structured approach ensures the AI uses all available context.

Setup guide

Set up Viesus 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 Viesus tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Viesus 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="Viesus Analyst",
        goal="Access and analyze Viesus data via MCP.",
        backstory="Expert analyst with direct Viesus access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Viesus 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 Viesus. 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 Viesus MCP in CrewAI

You pass the MCP server URL directly to your crew definition. The specialized agents then discover and use tools like `get_image_metadata` autonomously, without you having to write complex tool calling logic.

The server handles image processing metadata and job status. The crew can read technical details about the images using `get_image_metadata` before any enhancement occurs.

Yes. You can create a sequence where one agent reviews historical data (`list_processing_history`), decides the best course of action, and then another agent executes the enhancement job.

The setup requires defining which tools are available. You can use `tool_filter` to selectively expose only the necessary functions, keeping your system secure and focused.

This server touches image processing metadata and job status records. The crew manages the identifiers and technical details of the uploaded images throughout its lifecycle.

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