How do I find my Alegra API Token?

Log in to Alegra, navigate to **Settings** > **API**, and copy your token. You will need this along with your login email for Basic Authentication.

Can I filter contacts by type?

Yes! Use the `list_contacts` tool and specify the `type` parameter as either 'client' or 'provider' to filter your list.

Does this support checking stock levels?

Yes, the `list_inventory_items` tool provides real-time stock quantities for all your products and services managed in Alegra.

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

Name: Alegra
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Connect your Alegra account to your AI agent to unlock professional business management and automated invoicing. From creating and auditing sales invoices to monitoring real-time inventory levels and managing client/provider contact profiles, your agent handles your back-office operations through natural conversation.

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

Invoicing Orchestration — List, retrieve, and create professional sales invoices with tax compliance
Inventory Management — Monitor stock levels for products and services and retrieve technical metadata for items
Contact Oversight — List and manage client and provider profiles, ensuring your business network is always updated
Payment & Estimates — List payments and retrieve business estimates (cotizaciones) to track your revenue pipeline
Financial Insights — Quickly identify overdue invoices or low-stock items directly from your chat interface

The Alegra 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 Alegra to CrewAI via MCP

Follow these steps to integrate the Alegra 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 Alegra

Why Use CrewAI with the Alegra MCP Server

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

Alegra + CrewAI Use Cases

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

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

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

Alegra MCP Tools for CrewAI (10)

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

create_contact

Add a new contact

create_invoice

Add a new sales invoice

get_contact_details

Get contact metadata

get_invoice_details

Get invoice metadata

get_item_details

Get product metadata

list_contacts

List client/provider profiles

list_estimates

List business estimates

list_inventory_items

Check stock levels

list_invoices

Supports date filtering. List sales invoices

list_payments

List business payments

Example Prompts for Alegra in CrewAI

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

"List the last 5 invoices generated in Alegra."

"Show me the current stock for 'Office Chair v2'."

"List all contacts of type 'provider'."

Troubleshooting Alegra MCP Server with CrewAI

Common issues when connecting Alegra 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.

Alegra + CrewAI FAQ

Common questions about integrating Alegra 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.