Sigma MCP Server
An MCP server that provides Sigma rule validation and configuration capabilities for AI assistants. It enables users to validate Sigma detection rules against various validators and manage validator configurations through MCP tools and resources.
README
Sigma MCP Server
An MCP server that exposes pySigma functionality to AI assistants and other MCP clients.
Features
| Capability | Details |
|---|---|
Tool validate_rule |
Validate a Sigma rule (YAML) against all configured validators |
Tool configure_validators |
Persist a custom validator allow-list / exclusion-list for the current MCP session |
Resource sigma://validators |
JSON dict of available validator identifiers → descriptions |
Resource sigma://modifiers |
JSON list of available Sigma value modifier names |
Requirements
- Python ≥ 3.10
- Poetry (for development / installation)
Installation
git clone <repo-url>
cd sigma-mcp-server
poetry install
Usage
Running the server
poetry run sigma-mcp-server
# or, after installation:
sigma-mcp-server
The server listens on stdio by default (standard MCP transport).
Configuring in VS Code / Claude Desktop
Add the following entry to your MCP client configuration (e.g.
~/.config/claude/claude_desktop_config.json):
{
"mcpServers": {
"sigma": {
"command": "sigma-mcp-server"
}
}
}
Adjust the command path to the installed binary if it is not on PATH.
Tool Reference
validate_rule
Validate a single Sigma rule.
Arguments
| Name | Type | Description |
|---|---|---|
rule_yaml |
string |
Complete Sigma rule in YAML format |
Returns
A JSON array of validation issue objects. Each object contains:
| Key | Type | Description |
|---|---|---|
validator |
string |
Validator identifier that produced the issue |
type |
string |
Issue class name (e.g. IdentifierExistenceIssue) |
severity |
string |
low, medium, or high |
description |
string |
Human-readable description of the issue class |
rules |
array[string] |
Rule IDs / titles affected by the issue |
Additional subclass-specific fields (e.g. identifier) may also be present.
An empty array means the rule passed all active validators.
configure_validators
Persist a custom validator configuration for the current MCP session.
All subsequent validate_rule calls within the same session will use this
configuration.
Arguments
| Name | Type | Default | Description |
|---|---|---|---|
validator_names |
array[string] | null |
null |
Explicit allow-list of validator identifiers. null = use all. |
exclusions |
array[string] | null |
null (= []) |
Validator identifiers to exclude after the allow-list is applied. |
Returns
On success: {"validator_names": ..., "exclusions": [...]} confirming the stored config.
On error: {"error": "<description>"} when an unknown identifier is supplied.
Example – exclude a single validator:
{"exclusions": ["identifier_existence"]}
Example – use only two validators:
{"validator_names": ["identifier_existence", "identifier_uniqueness"]}
Resource Reference
sigma://validators
Returns a JSON object mapping validator identifier strings to their
human-readable descriptions. Validator identifiers are used with
configure_validators.
Example response (truncated):
{
"identifier_existence": "Checks if rule has identifier.",
"identifier_uniqueness": "Check rule UUID uniqueness.",
...
}
sigma://modifiers
Returns a sorted JSON array of Sigma value modifier names that can be used in
detection conditions (e.g. contains, startswith, re, base64).
Development
# Install dev dependencies
poetry install
# Run tests
poetry run pytest
# Run tests with coverage report
poetry run pytest --cov=sigma/mcp --cov-report=term-missing
# Type checking
poetry run mypy sigma/mcp/ tests/
# Code formatting
poetry run black sigma/ tests/ conftest.py
Test coverage must remain ≥ 95 %. All code must pass mypy --strict and be
formatted with black in its default configuration.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
E2B
Using MCP to run code via e2b.