Bring Siem
to Pydantic AI
Learn how to connect Wazuh (SIEM) to Pydantic AI and start using 21 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Wazuh (SIEM) MCP Server?
Connect your Wazuh SIEM to any AI agent to streamline security operations and endpoint monitoring through natural language.
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.
How it works
- Subscribe to this server
- Provide your Wazuh API URL, Username, and Password
- Start auditing your security environment from Claude, Cursor, or any MCP client
Who is this for?
- Security Analysts — quickly query agent status and FIM results without navigating the Wazuh dashboard
- DevSecOps Engineers — automate agent upgrades and monitor cluster health directly from terminal-based AI tools
- Incident Responders — fetch MITRE mappings and manager logs instantly during active investigations
Built-in capabilities (21)
Enroll a new Wazuh agent
Create a new Wazuh security role
Use WQL to specify which agents to delete. Remove Wazuh agents
Test rules and decoders against logs
Retrieve Wazuh manager logs
Get Wazuh manager daemon status
Supports WQL filtering. Get MITRE ATT&CK results
Supports WQL filtering. Get Rootcheck results
Supports WQL filtering. Get Security Configuration Assessment (SCA) results
Supports WQL filtering. Get File Integrity Monitoring (Syscheck) results
Supports WQL filtering. Get Syscollector inventory
Supports WQL filtering. List all Wazuh agents
List Wazuh cluster nodes
Supports WQL filtering. List loaded Wazuh decoders
Supports WQL filtering. List loaded Wazuh rules
List Wazuh API users
Restart Wazuh agents
Restart the Wazuh cluster
Update a Wazuh rule file
Update Wazuh security configuration
Upgrade Wazuh agents
Why Pydantic AI?
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.
- —
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Wazuh (SIEM) integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Wazuh (SIEM) connection logic from agent behavior for testable, maintainable code
Wazuh (SIEM) in Pydantic AI
Wazuh (SIEM) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Wazuh (SIEM) to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Wazuh (SIEM) in Pydantic AI
The Wazuh (SIEM) 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. All 21 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Wazuh (SIEM) for Pydantic AI
Every tool call from Pydantic AI to the Wazuh (SIEM) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I filter agents by specific operating systems or versions?
Yes! The list_agents tool supports WQL (Wazuh Query Language). You can use queries like os.name=ubuntu;os.version>18 to find specific endpoints.
How do I check for unauthorized file changes on my servers?
You can use the get_syscheck tool. It retrieves File Integrity Monitoring (FIM) results, allowing you to audit file modifications, deletions, or additions across your agents.
Is it possible to check the health of the Wazuh manager cluster?
Absolutely. Use get_manager_status to check daemon health or list_cluster_nodes to see the status of all nodes in your Wazuh cluster.
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.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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