How to Use the HackEDU (Security Journey) MCP in Pydantic AI

Q: Is the older MCPServerHTTP class still supported in Pydantic AI?

No, MCPServerHTTP is deprecated. You should use the unified MCPToolset class initialized with your Vinkius HTTP endpoint URL. This single class handles all connection mechanics for the 10 HackEDU MCP tools.

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Connect HackEDU (Security Journey) MCP to Pydantic AI

Create your Vinkius account to connect HackEDU (Security Journey) to Pydantic AI 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 HackEDU (Security Journey) with Pydantic AI

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Validate security training tasks with Pydantic AI

Eliminate silent API failures when managing your developer training. When your agent calls `create_issue` to assign a training module, Pydantic AI validates the response payload against strict Python schemas. If HackEDU returns unexpected data, the framework raises a validation error immediately. This guarantees that every training task assigned via `list_adaptive_training_plans` is correctly formatted. Your security pipelines run reliably without corrupting user profiles or triggering broken API calls.

Track team metrics using this MCP Server

Fetch user and team data with absolute certainty. The agent uses `get_team_progress` and `get_user_progress` to monitor how developers are doing. Because every data field is validated at runtime, you can write clean code that relies on exact integer completion percentages and string identifiers. If you need to list all active developers, `list_users` provides a structured list that matches your internal type definitions. This makes it simple to integrate progress tracking into your existing CI/CD dashboards.

Map vulnerability taxonomies without hallucinations

Ensure your agent maps security vulnerabilities to the correct lessons every time. The agent queries `list_vulnerabilities` to get the exact CWE and CVE mappings. By using Pydantic AI, the agent cannot hallucinate non-existent security codes or mismatch training modules. The agent then cross-references this with `list_content` to find the exact lesson. This strict validation means your automated security training pipeline only assigns highly relevant, verified lessons to your engineers.

Setup guide

Set up HackEDU (Security Journey) MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "hackedu-security-journey-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to HackEDU (Security Journey) tools.",
)

result = await agent.run("List recent HackEDU (Security Journey) transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HackEDU. 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 HackEDU (Security Journey) MCP in Pydantic AI

The framework validates every JSON response from tools like `list_vulnerabilities` and `list_users` against Pydantic models. If the HackEDU API changes its response structure, Pydantic AI fails loudly at runtime, preventing your agent from operating on corrupted or hallucinated data.

No, `MCPServerHTTP` is deprecated. You should use the unified `MCPToolset` class initialized with your Vinkius HTTP endpoint URL. This single class handles all connection mechanics for the 10 HackEDU MCP tools.

Yes, this framework is entirely model-agnostic. You can connect your HackEDU MCP tools to Anthropic, Gemini, or even local models. The type-safety features and tool validation work identically across all supported LLM providers.

This setup supports both Streamable HTTP and SSE (Server-Sent Events) transports. Since Vinkius hosts and manages the MCP server externally, you simply point your `MCPToolset` to the provided HTTP endpoint to begin.

Your team progress metrics, user lists, and vulnerability mappings are processed in ephemeral V8 MCP sandboxes. Vinkius handles the underlying API authentication token, ensuring that sensitive training records accessed via `get_team_progress` are never cached or exposed.

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