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autoRetouch MCP Server for CrewAIGive CrewAI instant access to 11 tools to Create Execution, Get Batch, Get Execution, and more

Built by Vinkius GDPR 11 Tools Framework

Connect your CrewAI agents to autoRetouch through Vinkius, pass the Edge URL in the `mcps` parameter and every autoRetouch tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The autoRetouch app connector for CrewAI is a standout in the Ecommerce category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
from crewai import Agent, Task, Crew

agent = Agent(
    role="autoRetouch Specialist",
    goal="Help users interact with autoRetouch effectively",
    backstory=(
        "You are an expert at leveraging autoRetouch 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 autoRetouch "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
autoRetouch
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 autoRetouch MCP Server

Connect your autoRetouch account to any AI agent and take full control of your automated image editing and high-fidelity retouching workflows through natural conversation.

When paired with CrewAI, autoRetouch becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call autoRetouch 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

  • Workflow Orchestration — Execute complex high-fidelity AI workflows for background removal, color correction, and shadow generation programmatically
  • Bulk Processing Intelligence — Programmatically upload raw images and monitor their processing status in real-time to maintain a perfectly coordinated media pipeline
  • Result Discovery — Retrieve high-fidelity result URLs for processed images and access detailed metadata for every individual execution
  • Lifecycle Management — Group multiple executions into tracked batches to oversee your organization's image editing volume efficiently
  • Financial Visibility — Access your organization's wallet balance and profile metadata directly through your agent for instant operational reporting

The autoRetouch MCP Server exposes 11 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 autoRetouch tools available for CrewAI

When CrewAI connects to autoRetouch through Vinkius, your AI agent gets direct access to every tool listed below — spanning photo-editing, background-removal, image-processing, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_execution

Returns the execution ID. Start an image processing execution

get_batch

Get details of a specific batch

get_execution

Get details of a specific execution

get_image

Get details of a specific image

get_organization

Get organization details

get_wallet_balance

Get account wallet balance

get_workflow

Get details of a specific workflow

list_batches

List all batches

list_executions

List recent executions

list_images

List uploaded images

list_workflows

List all image processing workflows

Connect autoRetouch to CrewAI via MCP

Follow these steps to wire autoRetouch into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 11 tools from autoRetouch

Why Use CrewAI with the autoRetouch MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with autoRetouch through the Model Context Protocol.

01

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

02

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

03

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

04

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

autoRetouch + CrewAI Use Cases

Practical scenarios where CrewAI combined with the autoRetouch MCP Server delivers measurable value.

01

Automated multi-step research: a reconnaissance agent queries autoRetouch for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

02

Scheduled intelligence reports: set up a crew that periodically queries autoRetouch, analyzes trends over time, and generates executive briefings in markdown or PDF format

03

Multi-source enrichment pipelines: chain autoRetouch tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

04

Compliance and audit automation: a compliance agent queries autoRetouch against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for autoRetouch in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with autoRetouch immediately.

01

"List all active image processing workflows in my organization."

02

"Run the 'Ghost Mannequin' workflow (ID: 'wf_123') on image ID 'img_456'."

03

"Check status and get the result URL for execution 'exec_789'."

Troubleshooting autoRetouch MCP Server with CrewAI

Common issues when connecting autoRetouch to CrewAI through the Vinkius, and how to resolve them.

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

autoRetouch + CrewAI FAQ

Common questions about integrating autoRetouch MCP Server with CrewAI.

01

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
02

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own 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.
03

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
04

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
05

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.