How do I generate my HackerOne API Token?

Log in to HackerOne, navigate to **Settings > API Token**, and click 'Create API Token'. Make sure to copy both the **Identifier** and the **Token Value** immediately.

Can I award bounties through this integration?

Yes! Use the `award_bounty` tool by providing the report ID and the amount. You can also specify an optional bonus amount for the researcher.

Does the integration support internal comments?

Yes, the `add_report_comment` tool has an optional `internal` boolean parameter (defaults to true). This allows you to communicate with your team privately on a specific report.

Can I filter reports by their handle or ID?

You can use `list_reports` to see all reports or `get_report` with a specific ID to retrieve detailed information for a single discovery.

HackerOne MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: HackerOne
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect HackerOne through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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

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({
        "hackerone": {
            "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 HackerOne, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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 HackerOne MCP Server

Connect your HackerOne organization account to any AI agent and take full control of your vulnerability management workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with HackerOne 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

Report Oversight — List all vulnerability reports, retrieve detailed information, and monitor their current state and severity.
Program Insights — Browse your bug bounty or VDP programs and access structured scopes and assets.
Report Interaction — Add comments to reports, change their triaged state, or award bounties directly from the chat.
Asset Tracking — Monitor the assets defined within your security programs and their reachability.
Financial Monitoring — Retrieve history of bounty payments and manage rewards efficiently.
Hacktivity Feed — Stay updated with the internal or public hacktivity feed to see recent discoveries.

The HackerOne 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 HackerOne to LangChain via MCP

Follow these steps to integrate the HackerOne 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 HackerOne via MCP

Why Use LangChain with the HackerOne MCP Server

LangChain provides unique advantages when paired with HackerOne through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine HackerOne 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 HackerOne queries for multi-turn workflows

HackerOne + LangChain Use Cases

Practical scenarios where LangChain combined with the HackerOne MCP Server delivers measurable value.

RAG with live data: combine HackerOne tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query HackerOne, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain HackerOne tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every HackerOne tool call, measure latency, and optimize your agent's performance

HackerOne MCP Tools for LangChain (10)

These 10 tools become available when you connect HackerOne to LangChain via MCP:

add_report_comment

Add a comment to a specific vulnerability report

award_bounty

Award a bounty for a vulnerability report

change_report_state

Update the state of a vulnerability report (e.g., triaged, resolved)

get_program

Get details for a specific security program

get_report

Get detailed information about a specific vulnerability report

list_assets

List assets defined in your security programs

list_hacktivity

List the HackerOne hacktivity feed

list_payments

List bounty payments history

list_programs

List bug bounty or VDP programs you have access to

list_reports

List vulnerability reports submitted to your HackerOne program

Example Prompts for HackerOne in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with HackerOne immediately.

"List all vulnerability reports submitted this week."

"Award a $500 bounty to report ID 12345."

"Change the state of report 12345 to 'Triaged'."

Troubleshooting HackerOne MCP Server with LangChain

Common issues when connecting HackerOne to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

HackerOne + LangChain FAQ

Common questions about integrating HackerOne MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.