How do I find which tables are available?

Use the `get_catalog` tool. It will return a list of all DataClasses (tables) exposed through the REST API in your 4D Server.

Can I filter data based on specific conditions?

Yes. Use the `list_entities` tool and provide an ORDA-style filter string in the `$filter` parameter (e.g., "status = 'active' AND price > 100").

Does this support creating new records?

Absolutely. Use the `create_entity` tool by providing the DataClass name and a JSON string containing the field data for the new record.

4D MCP Server for CrewAI 6 tools — connect in under 2 minutes

Name: 4D
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 6 Tools Framework

Connect your CrewAI agents to 4D through Vinkius, pass the Edge URL in the `mcps` parameter and every 4D 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="4D Specialist",
    goal="Help users interact with 4D effectively",
    backstory=(
        "You are an expert at leveraging 4D 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 4D "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 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 4D MCP Server

Bridge your 4D Server with the world of AI Agents through the power of ORDA (Object Relational Data Architecture). This integration transforms your 4D database into an intelligent, queryable knowledge base, allowing your AI agent to explore structures and manage records through natural conversation. No more manual REST calls; your agent can now audit catalogs, run complex entity queries, and perform high-speed CRUD operations, ensuring your 4D data is always accessible and actionable within your AI workflows.

When paired with CrewAI, 4D becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call 4D 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

Database Exploration — Retrieve the full catalog of DataClasses (tables) and their attribute definitions (fields) to map your data structure.
Advanced Querying — Perform complex data lookups using filters, ordering, and expansion of related entities with ORDA syntax.
CRUD Operations — Create, read, update, and delete records across any exposed DataClass in your 4D environment.
Metadata Insights — Check server information, version, and database structure on the fly to ensure system integrity.
Structured Access — Interact with your data using the modern ORDA model, ensuring consistency, type safety, and security.

The 4D MCP Server exposes 6 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 4D to CrewAI via MCP

Follow these steps to integrate the 4D 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 6 tools from 4D

Why Use CrewAI with the 4D MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with 4D 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

4D + CrewAI Use Cases

Practical scenarios where CrewAI combined with the 4D MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries 4D 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 4D, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain 4D 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 4D against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

4D MCP Tools for CrewAI (6)

These 6 tools become available when you connect 4D to CrewAI via MCP:

create_entity

Requires a JSON string representation of the data payload. Create a new record in the database

delete_entity

Delete a record from the database

get_catalog

Retrieve the database catalog definition

get_entity

Get a specific record by primary key

list_entities

Supports ORDA-style query parameters like $filter and $orderby for advanced lookups. Query records from a specific DataClass (table)

update_entity

Requires a JSON string payload. Update an existing record in the database

Example Prompts for 4D in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with 4D immediately.

"Show me the first 5 records from the 'Invoices' table."

"What tables (DataClasses) are exposed in my 4D catalog?"

"Create a new record in the 'Customers' table for 'John Doe' with email 'john@example.com'."

Troubleshooting 4D MCP Server with CrewAI

Common issues when connecting 4D 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.

4D + CrewAI FAQ

Common questions about integrating 4D 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.