How to Use the Wallarm MCP in Pydantic AI

Q: What can I use the Pydantic AI to do with Wallarm?

You can reliably list nodes using listfilteringnodes or track security issues by calling searchvulnerabilities. The strict typing ensures your agent handles the data correctly.

Q: How do I check for historical attacks with Wallarm and the pydantic-ai?

Run searchsecurityattacks to get a structured report on detected attack vectors. The Pydantic validation guarantees that even complex data sets are parsed correctly.

Q: Can I control vulnerability status with Wallarm and the pydantic-ai?

Yes, you call updatevulnerabilitystatus to change a flaw's lifecycle state. The structured nature of Pydantic guarantees you pass only valid statuses (open, closed, falsepositive).

Get guaranteed correct security actions on Wallarm using the Pydantic AI framework for reliable results.

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Connect Wallarm MCP to Pydantic AI

Create your Vinkius account to connect Wallarm 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 Wallarm with Pydantic AI

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Audit network access rules

Your agent needs to know what's allowed. Calling `list_ip_acl_rules` gives you a structured list of current IP allowlists and denylists. The response is guaranteed to match your Pydantic schema. This type safety means the data flowing into your application logic will always be correct, preventing silent bugs.

Find security vulnerabilities

Use `search_vulnerabilities` to get a list of open flaws from live traffic. Because the response is validated against Pydantic models, you know exactly what fields are present. If the API returns unexpected data, your agent fails loudly with an error—no silent corruption.

Manage attack rules

Need to modify access? `create_ip_acl_rule` lets you add IPs or CIDR ranges. You specify the list type ('white'/'black'), and the Pydantic validation ensures those arguments are correct before calling the tool. It makes complex configuration changes predictable.

Setup guide

Set up Wallarm 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": {
        "wallarm-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Wallarm transactions")
print(result.output)

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Common questions about Wallarm MCP in Pydantic AI

The Pydantic AI framework validates every MCP response against defined Python models at runtime. This means you get reliable, type-safe data from the Wallarm server.

You can reliably list nodes using `list_filtering_nodes` or track security issues by calling `search_vulnerabilities`. The strict typing ensures your agent handles the data correctly.

Run `search_security_attacks` to get a structured report on detected attack vectors. The Pydantic validation guarantees that even complex data sets are parsed correctly.

Yes, you call `update_vulnerability_status` to change a flaw's lifecycle state. The structured nature of Pydantic guarantees you pass only valid statuses (open, closed, falsepositive).

The server touches full request headers and payloads when you run `search_security_hits`. These are high-detail network packets that your agent must process carefully.

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