Bring Billing
to CrewAI
Learn how to connect Stigg to CrewAI and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the 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.
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.
How it works
- Subscribe to this server
- Enter your Stigg API Key
- Start managing your SaaS billing from Claude, Cursor, or any MCP-compatible client
No more jumping between dashboards to check a customer's entitlement or manually reporting usage. Your AI acts as a billing operations assistant.
Who is this for?
- Product Managers — instantly check customer plan statuses and feature entitlements without opening the Stigg console.
- Customer Success — provision trials or update customer details directly during support interactions.
- Developers — test billing flows and report usage for metered features straight from the terminal or IDE.
Built-in capabilities (12)
Get customer details via GraphQL
Get entitlements state via GraphQL
Provision a customer and optional subscription via GraphQL
Provision a subscription via GraphQL
Report usage via GraphQL
Cancel a subscription via REST API
Create a new customer via REST API
Create a subscription via REST API
Retrieve a customer via REST API
Retrieve a subscription via REST API
Report usage for metered features via REST API
Update a customer via REST API
Why CrewAI?
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.
- —
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
mcpsparameter 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 in CrewAI
Stigg and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Stigg to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Stigg in CrewAI
The Stigg 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. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Stigg for CrewAI
Every tool call from CrewAI to the Stigg MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I provision a customer and a subscription in one go?
Yes! Use the gql_provision_customer tool. It allows you to create the customer entity and optionally provide a planId to start their subscription immediately in a single GraphQL call.
How do I report usage for a metered feature?
You can use either rest_report_usage or gql_report_usage. Simply provide the customerId, the featureId, and the numeric value to update their metered usage in Stigg.
Is it possible to cancel an active subscription via the agent?
Yes, use the rest_cancel_subscription tool by providing the specific subscription ID. The agent will process the cancellation through Stigg's REST API.
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.
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.
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