How to Use the SimpleFatoora MCP in CrewAI

Q: How does SimpleFatoora integrate with crewai for invoicing?

You define an 'Invoice Crew' that uses createvatinvoice. The agents collaborate: one agent gathers the product data, and another executes the creation tool. It’s a full, multi-step operation.

Q: Can crewai manage SimpleFatoora customer records?

Yes. You can assign roles that use getcustomer, listcustomers, and updatecustomer together. The specialized agents handle the complexity of merging data sources.

Automate SimpleFatoora Operations with Specialized Agents using crewai.

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Setup SimpleFatoora with CrewAI

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Autonomous Invoice Processing Crew

You don't run one agent; you run a team. Assign an 'Invoice Agent' to call `create_simplified_invoice` and another 'Compliance Agent' to validate the required fields. The crew coordinates, ensuring every piece of data is checked before final submission. This setup moves beyond simple API calls—it simulates a human accounting department working together.

Specialized Customer Data Retrieval

Assign specialized roles: one agent to run `list_customers` and another to filter the results using `get_customer`. The collaboration ensures that if the list is massive, the second agent only processes what's necessary. The crew shares memory, so the agents pass context seamlessly without you writing complex state management.

Managed Product Syncing with MCP Server

Build an automated sync process. One agent gets the product list via `list_products`. A second agent then uses `update_product` or `create_product` based on internal business rules defined in its role. The resulting operation is self-monitoring; if a tool fails, the crew can escalate to a predefined recovery step.

Setup guide

Set up SimpleFatoora MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke SimpleFatoora tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="SimpleFatoora Analyst",
    goal="Access and analyze SimpleFatoora data via MCP.",
    backstory="Expert analyst with direct SimpleFatoora access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent SimpleFatoora transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="SimpleFatoora Analyst",
        goal="Access and analyze SimpleFatoora data via MCP.",
        backstory="Expert analyst with direct SimpleFatoora access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent SimpleFatoora transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by SimpleFatoora. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about SimpleFatoora MCP in CrewAI

You define an 'Invoice Crew' that uses `create_vat_invoice`. The agents collaborate: one agent gathers the product data, and another executes the creation tool. It’s a full, multi-step operation.

Yes. You can assign roles that use `get_customer`, `list_customers`, and `update_customer` together. The specialized agents handle the complexity of merging data sources.

You set up a 'Catalog Crew.' One agent checks for existing products using `get_product`, and another executes either `create_product` or `update_product` based on matching criteria.

Absolutely. The framework is designed for autonomy. If one agent hits a roadblock, the moderator agent can take over and attempt an escalation or retry mechanism.

The agents interact with Customer records, Product details, and Invoice documents. The workflow ensures these are handled in a coordinated fashion.

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