How to Use the Bugcrowd MCP in AutoGen

Let your AutoGen agents debate your security strategy. Use the Bugcrowd MCP Server to drive consensus-based vulnerability management.

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Connect Bugcrowd MCP to AutoGen

Create your Vinkius account to connect Bugcrowd to AutoGen 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 Bugcrowd with AutoGen

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Debate Bugcrowd findings in AutoGen

Assign a security agent to call `list_submissions` and a lead agent to review them. They debate the priority of each finding before acting. Use `get_target` to feed the conversation. Your agents challenge each other's assumptions about asset scope.

Consensus-driven actions for AutoGen

Once agents agree, use `create_submission` to log the result. The system only executes once the multi-agent group reaches a decision. Verify program requirements with `get_program`. Agents check if findings fit the rules before finalizing any report.

Streamable transport for AutoGen agents

The MCP Server handles schema conversion automatically. Your agents interact with the tools as if they were native functions. Deploy across stdio or HTTP. AutoGen maintains the conversation state while the server provides the data.

Setup guide

Set up Bugcrowd MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Bugcrowd tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Bugcrowd_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Bugcrowd data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Bugcrowd_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Bugcrowd data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bugcrowd. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Bugcrowd MCP in AutoGen

They call the tools as part of their conversation loop. One agent might request data, while another parses it to make a decision.

Absolutely. When the tool returns a high-severity finding, your agents can be programmed to trigger a review process.

It is designed for this. Multiple agents share the tool context, allowing for complex, collaborative workflows.

Use your endpoint token provided by Vinkius. The server manages the session so your agents never handle raw credentials.

It exposes your security program details, vulnerability submissions, and target lists. Each agent accesses only what it needs to perform its specific role.

Use it with your favorite AI tools

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