StackHawk MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect StackHawk through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"stackhawk": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using StackHawk, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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.
LangChain's ecosystem of 500+ components combines seamlessly with StackHawk through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 viastop_scan. - Risk Assessment — Effectively audit environments by listing operational scans with
list_scans, or retrieve deep vulnerability reports invokingget_alertstargeting specific scan iterations. - Application Management — Catalog active software deployments monitored by StackHawk utilizing
list_applications, and manage organizational parameters inspecting environments directly vialist_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 usingtriage_alert.
The StackHawk MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain 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 LangChain via MCP
Follow these steps to integrate the StackHawk MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from StackHawk via MCP
Why Use LangChain with the StackHawk MCP Server
LangChain provides unique advantages when paired with StackHawk through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine StackHawk MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across StackHawk queries for multi-turn workflows
StackHawk + LangChain Use Cases
Practical scenarios where LangChain combined with the StackHawk MCP Server delivers measurable value.
RAG with live data: combine StackHawk tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query StackHawk, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain StackHawk tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every StackHawk tool call, measure latency, and optimize your agent's performance
StackHawk MCP Tools for LangChain (10)
These 10 tools become available when you connect StackHawk to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting StackHawk to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersStackHawk + LangChain FAQ
Common questions about integrating StackHawk MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect StackHawk with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect StackHawk to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.