Veracode MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Veracode through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Veracode "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Veracode?"
)
print(result.data)
asyncio.run(main())
* 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 Veracode MCP Server
Equip your AI agent with complete read and write access to your Veracode ecosystem. Seamlessly blend application security posture management alongside your typical development workflow using entirely conversational AI.
Pydantic AI validates every Veracode tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Unified Vulnerability Tracing — Ask the agent to list Open security findings or mitigation statuses spanning across Static (SAST), Dynamic (DAST), and Component (SCA) analytics per application.
- Deep Flaw Details — Input specific Finding IDs and let the bot explain the underlying CWE error, affected code strings, severity ratings, and automated remediation tutorials.
- Portfolio AppSec Management — List tracked applications, create novel application profiles on the fly before a commit, or request health checks mapping sandbox testing environments.
- Dynamic Scan Queries — Poll your AI intuitively ensuring it retrieves the real-time execution bounds of your scheduled Web Application Security runtime scenarios.
The Veracode MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI 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 Veracode to Pydantic AI via MCP
Follow these steps to integrate the Veracode MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Veracode with type-safe schemas
Why Use Pydantic AI with the Veracode MCP Server
Pydantic AI provides unique advantages when paired with Veracode through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Veracode integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Veracode connection logic from agent behavior for testable, maintainable code
Veracode + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Veracode MCP Server delivers measurable value.
Type-safe data pipelines: query Veracode with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Veracode tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Veracode and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Veracode responses and write comprehensive agent tests
Veracode MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Veracode to Pydantic AI via MCP:
create_application
Provide the app schema and profile name as a JSON string. Create a new Veracode application profile container
delete_application
This action is irreversible. Delete a Veracode application permanently
get_api_health
Check the health of Veracode connection
get_application_details
Information includes its Veracode compliance policy status, business criticality rating, deployment state, and risk scores. Get a detailed profile of a Veracode application
get_finding_details
Explains the vulnerability type (CWE), affected source file, code path, and remediation guidance. Get precise vulnerability details for a specific flaw/finding
list_applications
Most structural entities return a globally unique GUID which is required for sub-resource lookups. List all Veracode AppSec Applications
list_dynamic_analyses
List configured Dynamic Analysis (DAST) scans
list_sandboxes
List all testing sandboxes linked to an application
list_security_findings
Retrieve the unified security findings for an application
list_veracode_users
Used to manage RBAC roles. List authorized Veracode identity users
Example Prompts for Veracode in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Veracode immediately.
"List all applications currently monitored in our Veracode account."
"Get the detailed security profile for the application GUID 'f3b9...'."
"Explain finding ID '89' from that app and how to fix it."
Troubleshooting Veracode MCP Server with Pydantic AI
Common issues when connecting Veracode to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiVeracode + Pydantic AI FAQ
Common questions about integrating Veracode MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Veracode with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Veracode to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.