Can I upscale an image to 4K resolution through the agent?

Yes! Use the `upscale_image_resolution` tool. You can specify the model (e.g., `photo` for realistic images) and the agent will instruct Claid AI to enhance the image to high resolution.

How do I check if my image processing task is finished?

Use the `get_processing_task_details` tool with the unique task ID. Your agent will fetch the current status and provide the output URL once the processing is complete.

Where do I find my Claid AI API Key?

Log in to your Claid.ai dashboard and navigate to the API or Settings section. You can generate and copy your API key from there.

Claid AI MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Claid AI
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Claid AI Specialist",
    goal="Help users interact with Claid AI effectively",
    backstory=(
        "You are an expert at leveraging Claid AI 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 Claid AI "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Claid AI MCP Server

Connect your Claid AI account to any AI agent and take full control of your image enhancement workflows through natural conversation. Transform basic product shots into professional photography instantly.

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

AI Enhancement — Apply multiple enhancements like HDR adjustment, white balance, and polishing natively
Resolution Upscaling — Increase image dimensions using specialized AI models for photos and digital art flawlessly
Background Logistics — Remove or replace backgrounds with white or custom scenes securely
Task Oversight — Monitor the status of async processing tasks and retrieve results flawlessly
Canvas Control — Resize images to specific dimensions with intelligent fit/fill logic flawlessly
Account Visibility — Retrieve core account information and monitor your AI usage quotas directly within your workspace

The Claid AI MCP Server exposes 8 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.

How to Connect Claid AI to CrewAI via MCP

Follow these steps to integrate the Claid AI MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

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

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Claid AI

Why Use CrewAI with the Claid AI MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Claid AI 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

Claid AI + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Claid AI 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 Claid AI, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Claid AI 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 Claid AI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Claid AI MCP Tools for CrewAI (8)

These 8 tools become available when you connect Claid AI to CrewAI via MCP:

enhance_image

You can combine multiple operations like upscale, background removal, and HDR adjustment. Apply AI enhancements and edits to an image

get_claid_account_info

Retrieve core account and quota information

get_processing_task_details

Get the status and result of an async image processing task

list_available_ai_operations

List common AI operations supported by the Claid API

list_claid_collections

List image collections in your account

list_claid_webhooks

List configured webhooks for async notifications

remove_image_background

Quickly remove or replace the background of an image

upscale_image_resolution

Increase image resolution using AI models

Example Prompts for Claid AI in CrewAI

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

"Upscale this product photo to high resolution: https://example.com/shoe.jpg"

"Remove the background from this image: https://example.com/model.jpg"

"What is the status of processing task 'task_98765'?"

Troubleshooting Claid AI MCP Server with CrewAI

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

MCP tools not discovered

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

Agent not using tools

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

Timeout errors

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

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.

Claid AI + CrewAI FAQ

Common questions about integrating Claid AI MCP Server with CrewAI.

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.

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.

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.

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.

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.