How to Use the Black Duck (Synopsys) MCP in Pydantic AI

Get type-safe dependency data in Pydantic AI. Validate your security findings against strict models at runtime.

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Connect Black Duck (Synopsys) MCP to Pydantic AI

Create your Vinkius account to connect Black Duck (Synopsys) 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 Black Duck (Synopsys) with Pydantic AI

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Validate Black Duck (Synopsys) data in Pydantic AI

Every tool response, including `get_vulnerability_details`, is checked against your Pydantic schemas. If the API returns garbage, the agent stops immediately. This prevents the common issue of agents hallucinating fields or failing silently on malformed JSON. You get reliable data for your security reports.

Manage project versions in Pydantic AI

Use `list_project_versions` to pull data into your typed models. Your agent logic relies on these validated structures to perform accurate risk assessments. It simplifies how you handle project metadata. By enforcing types, your agent code remains clean and free of defensive parsing logic.

Query scan locations via Pydantic AI

Call `list_code_locations` to identify exactly where your dependencies reside. The results are parsed and validated before your agent makes any decisions. This approach ensures that your agent operates only on valid, known data. It brings a new level of rigor to your open source supply chain monitoring.

Setup guide

Set up Black Duck (Synopsys) 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": {
        "black-duck-synopsys-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Black Duck (Synopsys) transactions")
print(result.output)

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Common questions about Black Duck (Synopsys) MCP in Pydantic AI

Use the MCPToolset class and pass it to your Agent definition. This links the server to your agent's toolset and enables runtime validation.

The framework validates every response. If an error occurs, it raises a validation exception that you can handle in your agent workflow.

Use SSE or Streamable HTTP. These are the standard, reliable ways to connect your agent to the external server.

Yes, you can share the same toolset across multiple agents. Each agent maintains its own type-safe validation boundary.

The server operates within a strictly firewalled environment. Your data is isolated per session, and the sandbox is wiped clean after each interaction to prevent data leakage.

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