Stigg MCP Server for CrewAIGive CrewAI instant access to 12 tools to Gql Get Customer, Gql Get Entitlements State, Gql Provision Customer, and more

Name: Stigg
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Connect your CrewAI agents to Stigg through Vinkius, pass the Edge URL in the `mcps` parameter and every Stigg tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The Stigg MCP Server for CrewAI is a standout in the Developer Tools category — giving your AI agent 12 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Stigg Specialist",
    goal="Help users interact with Stigg effectively",
    backstory=(
        "You are an expert at leveraging Stigg 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 Stigg "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

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

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About Stigg MCP Server

Connect your Stigg account to any AI agent to take full control of your pricing and packaging workflows. Manage the entire customer lifecycle from provisioning to usage reporting through natural conversation.

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

Customer Lifecycle — Create, update, and retrieve customer profiles using REST or GraphQL tools.
Subscription Management — Provision new subscriptions, fetch active plan details, or cancel them when needed.
Usage Reporting — Report metered feature usage in real-time to ensure accurate billing and entitlement enforcement.
Hybrid API Access — Choose between REST and GraphQL actions for flexible integration with your billing data.

The Stigg MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Stigg tools available for CrewAI

When CrewAI connects to Stigg through Vinkius, your AI agent gets direct access to every tool listed below — spanning billing, subscriptions, saas-pricing, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

gql

Gql get customer on Stigg

Get customer details via GraphQL

gql

Gql get entitlements state on Stigg

Get entitlements state via GraphQL

gql

Gql provision customer on Stigg

Provision a customer and optional subscription via GraphQL

gql

Gql provision subscription on Stigg

Provision a subscription via GraphQL

gql

Gql report usage on Stigg

Report usage via GraphQL

rest

Rest cancel subscription on Stigg

Cancel a subscription via REST API

rest

Rest create customer on Stigg

Create a new customer via REST API

rest

Rest create subscription on Stigg

Create a subscription via REST API

rest

Rest get customer on Stigg

Retrieve a customer via REST API

rest

Rest get subscription on Stigg

Retrieve a subscription via REST API

rest

Rest report usage on Stigg

Report usage for metered features via REST API

rest

Rest update customer on Stigg

Update a customer via REST API

Connect Stigg to CrewAI via MCP

Follow these steps to wire Stigg into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 12 tools from Stigg

Why Use CrewAI with the Stigg MCP Server

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

Stigg + CrewAI Use Cases

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

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

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

Example Prompts for Stigg in CrewAI

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

"Create a customer with ID 'cust_123', name 'Alice', and email 'alice@example.com' using REST."

"Report 50 units of usage for feature 'api-calls' for customer 'cust_123'."

"Get the details for customer 'cust_123' using GraphQL."

Troubleshooting Stigg MCP Server with CrewAI

Common issues when connecting Stigg to CrewAI through 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.

Stigg + CrewAI FAQ

Common questions about integrating Stigg 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.