Are scans executed locally or in the cloud?

Scans run on the StackHawk cloud infrastructure. The MCP integration only triggers and monitors them — no heavy processing happens in your AI context.

Why is the `login` step required?

The StackHawk API uses short-lived Bearer tokens. The `login` tool exchanges your API key for a session token that authenticates all subsequent requests.

Can the agent triage alerts automatically?

Yes. Use `triage_alert` to mark specific vulnerabilities as false positives, accepted risks, or confirmed issues. Each triage action targets a single alert by ID.

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

Name: StackHawk
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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 StackHawk MCP Server

Integrate the robust dynamic application security testing (DAST) capabilities of StackHawk directly into your conversational AI. Empower your engineering team to monitor system vulnerabilities, initiate complex scans, and orchestrate proactive security protocols without relying heavily on static dashboards. Connect securely to your workspaces, instruct your AI to assess ongoing security threats, and automatically classify alerts through a natural language interface designed to accelerate risk remediation across modern CI/CD pipelines.

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

Automated Scanning — Programmatically initiate comprehensive security evaluations across your environments utilizing run_scan, and halt operations securely targeting specific execution UUIDs via stop_scan.
Risk Assessment — Effectively audit environments by listing operational scans with list_scans, or retrieve deep vulnerability reports invoking get_alerts targeting specific scan iterations.
Application Management — Catalog active software deployments monitored by StackHawk utilizing list_applications, and manage organizational parameters inspecting environments directly via list_environments.
Triage & Operations — Authenticate securely establishing a valid operational bearer token with login, and instruct the AI to accurately qualify, dismiss, or assign statuses prioritizing critical mitigation efforts using triage_alert.

The StackHawk 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 StackHawk to CrewAI via MCP

Follow these steps to integrate the StackHawk 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 StackHawk

Why Use CrewAI with the StackHawk MCP Server

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

StackHawk + CrewAI Use Cases

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

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

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

StackHawk MCP Tools for CrewAI (10)

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

get_application_details

Get detailed configuration for a specific StackHawk application

get_organization_details

Get StackHawk organization details and subscription tier

get_scan_alerts

Download individual security alerts discovered by a DAST scan

get_scan_results

Get detailed results and metadata for a specific DAST scan

list_api_keys

Useful for auditing and hygiene. List API keys configured for a StackHawk organization

list_applications

Requires a Bearer token and organization ID. List all registered DAST applications in a StackHawk organization

list_environments

g., Development, Staging, Production) configured on the application. List configured scan environments for a StackHawk application

list_scans

Includes scan IDs and high-level alert counts. List all DAST scan executions for a StackHawk application

login

This token is required for all subsequent StackHawk tool calls. Authenticate and obtain a Bearer access token from StackHawk

triage_alert

Valid statuses: RISK_ACCEPTED, FALSE_POSITIVE, IN_PROGRESS. Triage a DAST security alert (accept risk, false positive, etc.)

Example Prompts for StackHawk in CrewAI

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

"Log in with my API token, list my projects and environments, then show the critical vulnerabilities from the latest scan."

"Run a new scan against the Production application."

Troubleshooting StackHawk MCP Server with CrewAI

Common issues when connecting StackHawk 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.

StackHawk + CrewAI FAQ

Common questions about integrating StackHawk 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.