How do I get a ContentKing API Key?

Log in to ContentKing, go to **Account Settings > API**, and click **Create API Key**. Copy the key and paste it into the field below.

Can the agent make changes to my SEO settings?

No. The integration operates in read-only mode. It reads metrics, lists alerts, and retrieves data for analysis, but cannot modify any SEO settings or configurations.

What types of metrics can I check?

You can fetch domain health scores, tracked URL counts, active alerts by severity, page load times, and summaries of issues found during the latest crawls.

ContentKing MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: ContentKing
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to ContentKing through Vinkius, pass the Edge URL in the `mcps` parameter and every ContentKing 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

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="ContentKing Specialist",
    goal="Help users interact with ContentKing effectively",
    backstory=(
        "You are an expert at leveraging ContentKing 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 ContentKing "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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* 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 ContentKing MCP Server

Integrate your AI with ContentKing, the real-time SEO auditing and monitoring platform.

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

Site Audits — Review crawled pages and identify active SEO risks or technical errors instantly.
Change Monitoring — Get summaries of recent alerts or infrastructure changes impacting SEO.
Metric Retrieval — Fetch health scores and page-level data for your reporting workflows.

The ContentKing MCP Server exposes 10 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 ContentKing to CrewAI via MCP

Follow these steps to integrate the ContentKing 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 10 tools from ContentKing

Why Use CrewAI with the ContentKing MCP Server

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

ContentKing + CrewAI Use Cases

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

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

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

ContentKing MCP Tools for CrewAI (10)

These 10 tools become available when you connect ContentKing to CrewAI via MCP:

get_active_alerts

Get active monitoring alerts for a website

get_issue_details

Get details for a specific SEO issue

get_portfolio_summary

Get a high-level health summary across all websites

get_website_health

Get current health score and status for a website

list_monitored_pages

List monitoring data for pages on a website

list_seo_issues

List SEO issues for a website

list_websites

List all websites monitored in ContentKing

notify_page_update

Notify ContentKing of page updates to trigger re-crawl

notify_sitemap_update

Notify ContentKing that a sitemap has been updated

search_pages_by_url

Search for monitored pages by URL keyword

Example Prompts for ContentKing in CrewAI

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

"Get the current health score for 'vinkius.com'."

"List all critical alerts for meta tag changes today."

"Give me a high-level summary of the health of all my monitored websites."

Troubleshooting ContentKing MCP Server with CrewAI

Common issues when connecting ContentKing 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.

ContentKing + CrewAI FAQ

Common questions about integrating ContentKing 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.