Wazuh (SIEM) MCP Server for Pydantic AIGive Pydantic AI instant access to 21 tools to Create Agent, Create Security Role, Delete Agents, and more

Name: Wazuh (SIEM)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Wazuh (SIEM) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Wazuh (SIEM) MCP Server for Pydantic AI is a standout in the Fort Knox category — giving your AI agent 21 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

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 Wazuh (SIEM) "
            "(21 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Wazuh (SIEM)?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Wazuh (SIEM) MCP Server

Connect your Wazuh SIEM to any AI agent to streamline security operations and endpoint monitoring through natural language.

Pydantic AI validates every Wazuh (SIEM) tool response against typed schemas, catching data inconsistencies at build time. Connect 21 tools through 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

Agent Management — List all enrolled agents, create new ones, and perform bulk actions like restarts or upgrades using WQL filtering.
Manager & Cluster Health — Monitor manager daemon status, fetch logs, and inspect cluster nodes to ensure high availability.
Security Auditing — Query File Integrity Monitoring (Syscheck), Security Configuration Assessment (SCA), and Rootcheck results.
Threat Intelligence — Access MITRE ATT&CK mappings and test log decoders to validate your detection pipeline.
Rule Orchestration — List and update rules or decoders directly to fine-tune your security posture.

The Wazuh (SIEM) MCP Server exposes 21 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 21 Wazuh (SIEM) tools available for Pydantic AI

When Pydantic AI connects to Wazuh (SIEM) through Vinkius, your AI agent gets direct access to every tool listed below — spanning siem, threat-detection, vulnerability-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create agent on Wazuh (SIEM)

Enroll a new Wazuh agent

create

Create security role on Wazuh (SIEM)

Create a new Wazuh security role

delete

Delete agents on Wazuh (SIEM)

Use WQL to specify which agents to delete. Remove Wazuh agents

get

Get logtest on Wazuh (SIEM)

Test rules and decoders against logs

get

Get manager logs on Wazuh (SIEM)

Retrieve Wazuh manager logs

get

Get manager status on Wazuh (SIEM)

Get Wazuh manager daemon status

get

Get mitre on Wazuh (SIEM)

Supports WQL filtering. Get MITRE ATT&CK results

get

Get rootcheck on Wazuh (SIEM)

Supports WQL filtering. Get Rootcheck results

get

Get sca on Wazuh (SIEM)

Supports WQL filtering. Get Security Configuration Assessment (SCA) results

get

Get syscheck on Wazuh (SIEM)

Supports WQL filtering. Get File Integrity Monitoring (Syscheck) results

get

Get syscollector on Wazuh (SIEM)

Supports WQL filtering. Get Syscollector inventory

list

List agents on Wazuh (SIEM)

Supports WQL filtering. List all Wazuh agents

list

List cluster nodes on Wazuh (SIEM)

List Wazuh cluster nodes

list

List decoders on Wazuh (SIEM)

Supports WQL filtering. List loaded Wazuh decoders

list

List rules on Wazuh (SIEM)

Supports WQL filtering. List loaded Wazuh rules

list

List security users on Wazuh (SIEM)

List Wazuh API users

restart

Restart agents on Wazuh (SIEM)

Restart Wazuh agents

restart

Restart cluster on Wazuh (SIEM)

Restart the Wazuh cluster

update

Update rule file on Wazuh (SIEM)

Update a Wazuh rule file

update

Update security config on Wazuh (SIEM)

Update Wazuh security configuration

upgrade

Upgrade agents on Wazuh (SIEM)

Upgrade Wazuh agents

Connect Wazuh (SIEM) to Pydantic AI via MCP

Follow these steps to wire Wazuh (SIEM) into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 21 tools from Wazuh (SIEM) with type-safe schemas

Why Use Pydantic AI with the Wazuh (SIEM) MCP Server

Pydantic AI provides unique advantages when paired with Wazuh (SIEM) 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 Wazuh (SIEM) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Wazuh (SIEM) connection logic from agent behavior for testable, maintainable code

Wazuh (SIEM) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Wazuh (SIEM) MCP Server delivers measurable value.

Type-safe data pipelines: query Wazuh (SIEM) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Wazuh (SIEM) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Wazuh (SIEM) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Wazuh (SIEM) responses and write comprehensive agent tests

Example Prompts for Wazuh (SIEM) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Wazuh (SIEM) immediately.

"List all Wazuh agents that are currently active."

"Show me the latest Security Configuration Assessment (SCA) results."

"Check the Wazuh manager logs for any recent errors."

Troubleshooting Wazuh (SIEM) MCP Server with Pydantic AI

Common issues when connecting Wazuh (SIEM) to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Wazuh (SIEM) + Pydantic AI FAQ

Common questions about integrating Wazuh (SIEM) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Wazuh (SIEM) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.