How do I get an Elemeno API Key?

Log in to your Elemeno dashboard, select your project, navigate to **Settings > API**, and you can retrieve your unique API Key from there.

Does the integration support draft content?

Yes, you can use the list_collection_items tool to see all items, including their status (e.g., draft or published). Specific content retrieval depends on your API key permissions.

Can the agent update content via the API?

This integration currently focuses on listing and auditing content. Creating or updating items and singletons should be managed via the Elemeno dashboard or specific management API endpoints.

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

Name: Elemeno
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Elemeno through Vinkius, pass the Edge URL in the `mcps` parameter and every Elemeno 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="Elemeno Specialist",
    goal="Help users interact with Elemeno effectively",
    backstory=(
        "You are an expert at leveraging Elemeno 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 Elemeno "
        "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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Ed25519Audit chain

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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 Elemeno MCP Server

Integrate Elemeno, the headless CMS designed for developers, directly into your AI workflow. Manage your content collections and singletons (global pages), track individual items and their publishing statuses, monitor field schemas, and oversee your entire content library using natural language.

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

Collection Oversight — List and retrieve detailed information and field schemas for all your content collections.
Content Intelligence — Monitor individual collection items, resolving titles, slugs, and real-time publishing statuses.
Singleton Management — Access and monitor singleton content blocks, resolving global settings and unique page data.
Content Auditing — Retrieve high-level summaries of collection activity, item counts, and organizational CMS health.

The Elemeno 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 Elemeno to CrewAI via MCP

Follow these steps to integrate the Elemeno 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 Elemeno

Why Use CrewAI with the Elemeno MCP Server

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

Elemeno + CrewAI Use Cases

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

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

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

Elemeno MCP Tools for CrewAI (10)

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

get_collection_details

Get detailed settings and field schema for a specific collection

get_collection_item_details

Get full content and metadata for a specific item in a collection

get_elemeno_account_metadata

Retrieve metadata and limits for your Elemeno account

get_singleton_content

Get the full content data for a specific singleton

list_collection_items

List all content items within a specific collection

list_content_collections

List all content collections configured in your Elemeno account

list_content_singletons

List all singleton content blocks (unique global pages/settings)

list_published_content

Identify items that are currently in a "Published" status

quick_content_volume_audit

Retrieve a high-level summary of collection and singleton activity

search_collection_content

Search for items within a collection using a title or slug keyword

Example Prompts for Elemeno in CrewAI

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

"List all content collections in my project."

"Show me the items in the 'Services' collection."

"What is the content of the 'Contact Page' singleton?"

Troubleshooting Elemeno MCP Server with CrewAI

Common issues when connecting Elemeno 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.

Elemeno + CrewAI FAQ

Common questions about integrating Elemeno 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.