How to Use the 42Crunch MCP in LangChain

Q: Can 42Crunch trigger audits within a LangChain chain?

Yes, you use the triggeraudit tool as a step in your execution flow. The agent waits for the audit result to determine if the next node in the chain should run.

Q: How do I handle multiple API collections in LangChain?

Use listcollections to retrieve IDs, then pass those identifiers to subsequent tools. It lets your agent navigate complex multi-project environments.

Chain your API security audits directly into LangChain workflows for automated, logic-driven vulnerability management.

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Connect 42Crunch MCP to LangChain

Create your Vinkius account to connect 42Crunch to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup 42Crunch with LangChain

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Automated security checks in LangChain

Trigger security audits the moment a new API definition hits your repository. You can use `trigger_audit` inside a LangGraph node to verify specs before any deployment happens. Your agent inspects the resulting data from `get_audit_report` to decide if the build pipeline should proceed. It turns security into a conditional step within your chain.

Manage your API inventory via LangChain

Map out your entire platform architecture by calling `list_collections` and `list_apis`. Your agents build a mental model of your API surface area without manual input. Every `get_api` call fetches detailed metadata, letting the agent cross-reference security scores with your internal documentation. It keeps your security state visible to the entire pipeline.

Dynamic conformance testing with LangChain

Run live scans against deployed endpoints using `list_scans` and `get_scan_report`. The agent evaluates the output to ensure your actual traffic matches the defined security contract. This MCP Server provides the raw data your agents need to catch drift between your OpenAPI specs and real-world behavior. It makes security verification a native part of your LangChain agent's logic.

Setup guide

Set up 42Crunch MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes 42Crunch tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "42crunch-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent 42Crunch transactions"
    })
    print(result["messages"][-1].content)

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Common questions about 42Crunch MCP in LangChain

You connect the server as a tool resource within your LangGraph nodes. The agents then invoke specific functions like `import_api` to interact with your platform directly.

Yes, you use the `trigger_audit` tool as a step in your execution flow. The agent waits for the audit result to determine if the next node in the chain should run.

Every tool call returns JSON that maps perfectly to LangSmith traces. You get full visibility into the inputs and outputs of every audit request your agent makes.

Use `list_collections` to retrieve IDs, then pass those identifiers to subsequent tools. It lets your agent navigate complex multi-project environments.

Your OpenAPI definitions and security reports stay within your configured platform instance. The MCP Server only transmits the specific data points your agent requests to perform its security assessment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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