NGSIEM MCP Server

A Model Context Protocol (MCP) server that provides programmatic access to CrowdStrike NGSIEM search capabilities. This server enables MCP-compatible applications to execute security event searches through a standardized interface.

Overview

This MCP server acts as an intelligent bridge between LLMs and CrowdStrike NGSIEM, designed to prevent hallucinations and enforce query integrity. It exposes NGSIEM functionality through ten specialized tools that prioritize validation and context awareness.

Quick Start

Prerequisites

• Python 3.13+
• CrowdStrike API credentials with NGSIEM scope
• MCP-compatible client application

Installation

1. Clone and setup environment:

   cd /path/to/cs-ngsiem-mcp
   python3 -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt
   

2. Configure Environment Variables:

   Create a .env file in the root directory:

   cp .env.example .env
   

   Add your CrowdStrike API credentials (ensure NGSIEM and Falcon Data Replicator scopes are enabled):

   #.env
   CROWDSTRIKE_CLIENT_ID=your_client_id_here
   CROWDSTRIKE_CLIENT_SECRET=your_client_secret_here
   CROWDSTRIKE_BASE_URL=https://api.eu-1.crowdstrike.com
   NGSIEM_DEFAULT_REPOSITORY=base_sensor
   LOG_LEVEL=INFO
   

3. Configure Repositories:

   Create the repository catalog file config/repositories.yaml:

   cp config/repositories.example.yaml config/repositories.yaml
   

   The repositories.yaml format allows you to define schema and context for each repository:

   repositories:
     - name: "base_sensor"
       description: "Telemetry events from Falcon sensors (process, network, file)"
       default: true
       data_types:
         - "ProcessRollup2"
         - "NetworkConnectIP4"
       use_cases:
         - "Threat hunting"
         - "Incident investigation"
         
     - name: "audit_logs"
       description: "Falcon platform audit logs"
       default: false
   

   Tip: You can use the get_repo_fieldset tool to discover available fields in any configured repository.

Key Capabilities

1. Intelligent Query Validation: Before any search is executed, the Query Validator analyzes the syntax to catch common errors. It checks for balanced parentheses, valid operators, and correct function usage, ensuring that only syntactically correct queries are sent to the API.

2. Dynamic Schema Discovery (Field Validation): To prevent the LLM from hallucinating non-existent fields, the server provides the get_repo_fieldset tool. This tool dynamically downloads the live schema (all valid fields) for a specific repository from your environment. The LLM is instructed to always consult this schema before constructing a query.

3. Context-Aware Repository Management: The server does not guess where logs are securely stored. You explicitly define your log sources in config/repositories.yaml. This configuration file tells the LLM exactly which repository contains what data (e.g., "base_sensor" repository for process events, "squid" repository for proxy logs), allowing it to intelligently select the right data source for each question.

graph TD
    A[LLM Query] --> B{Schema Check}
    B -->|get_repo_fieldset| C[Download Live Fields]
    C --> D[Construct Query]
    D --> E{Syntax Check}
    E -->|validate_query| F[Execute Search]
    
    style A fill:#e1f5ff
    style B fill:#fff3e0
    style E fill:#fff3e0
    style F fill:#e8f5e9

HTTP Server Mode (FastAPI + SSE)

For production deployments or remote access, the server supports the MCP 2025-11-25 Streamable HTTP transport.

📄 Read the Full Architecture & Feature Guide for detailed diagrams and flows.

📄 Read the Full Query Validation Architecture for detailed diagrams and flows.

Quick Start (HTTP)

1. Configure API Key: Add MCP_API_KEY to your .env file (generated automatically if missing, but better to set it).

2. Start the Server: Use the provided script which handles environment loading and logging on Mac or Linux:

   ./start_http_server.sh
   

   or on Windows:

   ./start_http_server.ps1
   

3. Verify Connection (Optional): Use the Inspector script to test the server:

   ./start_http_inspector.sh
   

Claude Desktop Integration

To connect Claude Desktop to the HTTP server, you must use a proxy to inject the authentication headers.

Update your claude_desktop_config.json:

{
  "mcpServers": {
    "ngsiem-http": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "http://localhost:8080/mcp",
        "--header",
        "Authorization: Bearer <YOUR_MCP_API_KEY_LOCATED_IN_YOUR .env FILE>"
      ]
    }
  }
}

VS Code Integration

For VS Code users (using extensions like Cline or Roo Code), the configuration uses the native HTTP transport directly without the need for a proxy.

Update your MCP settings in VS Code:

{
  "servers": {
    "cs-ngsiem-mcp": {
      "type": "http",
      "url": "http://localhost:8080/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_AUTH_TOKEN>"
      }
    }
  }
}

See SERVER_ARCHITECTURE.md for detailed configuration options.

Architecture

For a detailed breakdown of the system architecture, request flows, and component diagrams, please refer to:

👉 SERVER_ARCHITECTURE.md

Available Tools

Tool Workflow

This diagram illustrates the typical user journey from discovering repositories to executing searches.

graph TD
    Start[User Goal] --> KnowRepo{Know Config?}
    
    KnowRepo -->|No| ListRepos[get_available_repositories]
    ListRepos --> ChooseRepo[Select Repository]
    KnowRepo -->|Yes| ChooseRepo
    
    ChooseRepo --> NeedQuery{Need Query?}
    
    NeedQuery -->|Yes| BrowseTemplates[list_templates]
    BrowseTemplates --> BuildQuery[build_query]
    BuildQuery --> Validate[validate_query]
    
    NeedQuery -->|No| Validate
    
    Validate -->|Valid| Execution{Execution Mode}
    Validate -->|Invalid| BuildQuery
    
    Execution -->|Async| StartSearch[start_search]
    Execution -->|Blocking| SearchWait[search_and_wait]
    
    StartSearch --> Poll[get_search_status]
    Poll -->|Running| Poll
    Poll -->|Done| Results[Get Results]
    
    SearchWait --> Results
    
    style ListRepos fill:#fff3e0
    style BrowseTemplates fill:#fff3e0
    style BuildQuery fill:#fff3e0
    style Validate fill:#fff3e0
    style StartSearch fill:#e8f5e9
    style SearchWait fill:#e8f5e9

1. get_available_repositories

Get the list of configured NGSIEM repositories.

Parameters: None

Returns: List of repositories with descriptions, data types, and use cases.

Use Case: Discovery of available data sources before searching.

2. start_search

Initiates an asynchronous NGSIEM search.

Parameters:

• repository (string, optional): Repository name (defaults to .env config)
• query_string (string, required): NGSIEM query syntax
• start (string, optional): Time range (default: "1d")
• is_live (boolean, optional): Live search mode (default: false)

Returns: Search job ID for status polling

Use Case: Long-running searches where client wants progress control

Example Query:

#event_simpleName=ProcessRollup2 | FileName=powershell.exe

3. get_search_status

Retrieves status and results of a running search.

Parameters:

• repository (string, optional): Repository name
• search_id (string, required): ID from start_search

Returns: Status, event count, and results (if complete)

Use Case: Polling for search completion

4. search_and_wait

Executes search and waits for completion (blocking operation).

Parameters:

• repository (string, optional): Repository name
• query_string (string, required): NGSIEM query
• start (string, optional): Time range (default: "1d")
• is_live (boolean, optional): Live search mode (default: false)
• max_wait_seconds (integer, optional): Timeout (default: 300, max: 3600)
• poll_interval (integer, optional): Poll frequency (default: 2s)

Returns: Complete results or timeout error

Use Case: Quick searches with immediate results needed

Internal Flow:

graph LR
    A[search_and_wait] --> B[start_search]
    B --> C{Poll Loop}
    C -->|done=false| D[sleep poll_interval]
    D --> E[get_search_status]
    E --> C
    C -->|done=true| F[Return Results]
    C -->|timeout| G[Raise TimeoutError]
    
    style F fill:#e8f5e9
    style G fill:#ffebee

5. stop_search

Cancels a running search.

Parameters:

• repository (string, optional): Repository name
• search_id (string, required): ID to cancel

Returns: Cancellation confirmation

Use Case: Terminating long-running searches

6. get_query_reference

Access NGSIEM query language documentation.

Parameters:

• category (string, optional): Filter by category (aggregate, filtering, security, etc.)
• function_name (string, optional): Get details for specific function
• search_term (string, optional): Search functions by keyword

Returns: Function documentation with syntax and examples

Use Case: Discover available functions before building queries

7. list_templates

Browse pre-built security query templates.

Parameters:

• category (string, optional): Filter by category (threat_hunting, ioc_hunting, etc.)
• search_term (string, optional): Search templates by keyword

Returns: Available templates with descriptions and MITRE ATT&CK mapping

Use Case: Find ready-to-use queries for common security operations

8. validate_query

Validate query syntax before execution.

Parameters:

• query (string, required): NGSIEM query to validate
• strict (boolean, optional): Treat warnings as errors

Returns: Validation result with issues and suggestions

Use Case: Catch syntax errors before running searches

9. build_query

Build queries from templates with parameters.

Parameters:

• template (string, required): Template name to use
• parameters (object, optional): Values for template placeholders

Returns: Generated query ready for execution

Use Case: Create customized queries from templates

10. get_repo_fieldset

MANDATORY FIRST STEP: Discover all available fields in a NGSIEM repository.

Important: Call this tool BEFORE constructing any search query. Only use field names returned by this tool in your queries.

Parameters:

• repository (string, optional): Repository name (uses default from config if not specified)
• timeout_seconds (integer, optional): Maximum wait time (1-120 seconds, default: 60)

Returns: Complete list of valid field names for the repository

Use Case: Schema discovery to prevent query failures from invalid field references

Security: Repository name is validated against injection attacks (alphanumeric, underscores, hyphens only)

11. get_query_best_practices

Get NGSIEM query writing best practices for optimal performance.

Parameters: None

Returns:

• 8-step query construction pipeline (based on Humio/LogScale documentation)
• Optimization tips (tag specificity, limit placement, case sensitivity)
• Efficient patterns with examples
• Anti-patterns to avoid

Use Case: Learn how to structure queries for maximum efficiency

Query Pipeline (execute in order):

tag-filters | field-filters | transformations | aggregate | visualization

1. Narrow Timeframe - Reduce search scope
2. Tag Filters First - Use #field syntax for indexed fields (30x faster)
3. Field Value Filters - Filter by specific values
4. Exclusion Filters - Remove unwanted results
5. Regex Filters - Pattern matching (use sparingly)
6. Transformations - eval, format, parse functions
7. Aggregations - count, sum, groupBy, etc.
8. Visualization - sort, table, head for output

Available Resources

ngsiem://repositories

A JSON-formatted resource providing detailed metadata about all configured repositories.

Content:

[
  {
    "name": "base_sensor",
    "description": "Main event stream",
    "data_types": ["ProcessRollup2", "DnsRequest"],
    "use_cases": ["General threat hunting", "Process analysis"]
  }
]

Usage:

• Claude Desktop: Automatically reads this on startup to understand the environment.
• Manual: Use read_resource("ngsiem://repositories") to inspect config.

Project Structure

cs-ngsiem-mcp/
├── ngsiem_mcp_stdio.py      # MCP stdio server implementation
├── ngsiem_mcp_http.py       # MCP HTTP server implementation
├── ngsiem_tools.py           # NGSIEM API wrapper
├── ngsiem_query_catalog.py   # Query function/template catalog
├── ngsiem_query_validator.py # Query syntax validator
├── config.py                 # Configuration management
├── config/                   # Query catalogs
│   ├── ngsiem_functions.yaml # 54 NGSIEM functions
│   ├── ngsiem_syntax.yaml    # Query syntax reference
│   └── ngsiem_templates.yaml # 32 security templates
├── .env                      # Credentials (gitignored)
├── .env.example              # Configuration template
├── requirements.txt          # Python dependencies
└── README.md                 # This file

Module Dependencies

graph TD
    A[ngsiem_mcp_http.py] --> B[ngsiem_tools.py]
    A --> C[config.py]
    B --> C
    C --> D[.env]
    B --> E[falconpy.APIHarnessV2]
    A --> F[mcp.server]
    
    A:::server
    B:::tools
    C:::config
    D:::env
    E:::external
    F:::external
    
    classDef server fill:#34a853,color:#fff
    classDef tools fill:#fbbc04
    classDef config fill:#4285f4,color:#fff
    classDef env fill:#ea4335,color:#fff
    classDef external fill:#9e9e9e,color:#fff

Security Architecture

graph LR
    A[Client Input] -->|Pydantic| B[Validation Layer]
    B -->|Sanitization| C[Query Builder]
    C -->|OAuth2| D[API Request]
    D -->|TLS 1.2+| E[CrowdStrike API]
    
    B -.->|Invalid| F[Error Response]
    D -.->|Auth Fail| F
    
    style A fill:#e1f5ff
    style B fill:#e8f5e9
    style C fill:#fff4e1
    style E fill:#fce4ec
    style F fill:#ffebee

Security Features

• No hardcoded credentials: All secrets in .env
• Input validation: Pydantic models with strict typing
• Query sanitization: Prevents injection attacks
• OAuth2 authentication: Automatic token management
• Audit logging: Detailed operation logs
• Error handling: No sensitive data in error messages

Configuration

Environment Variables

Variable	Description	Example	Required
CROWDSTRIKE_CLIENT_ID	API Client ID	abc123...	Yes
CROWDSTRIKE_CLIENT_SECRET	API Secret	xyz789...	Yes
CROWDSTRIKE_BASE_URL	API Endpoint	https://api.eu-1.crowdstrike.com	Yes
NGSIEM_DEFAULT_REPOSITORY	Default Repository	base_sensor	Yes
LOG_LEVEL	Logging Level	INFO	No
LOG_FILE	Log File Path (Stdio Mode)	ngsiem_mcp.log	No
HTTP Server Config
MCP_API_KEY	Bearer Token for Auth	secret-token-123	Yes (HTTP)
MCP_HTTP_HOST	Server Host	0.0.0.0	No
MCP_HTTP_PORT	Server Port	8080	No
MCP_HTTP_ACCESS_LOG	Uvicorn Access Log Path	ngsiem-mcp-http.log	No
MCP_HTTP_APP_LOG	Application Log Path	ngsiem-mcp-app.log	No
MCP_CORS_ORIGINS	CORS Allowed Origins	* or http://localhost:3000	No
NGSIEM_THREAD_POOL_SIZE	Max threads for blocking API calls	4	No
MCP_SKIP_AUTH	Bypass auth for dev testing	true	No

Note: MCP_SKIP_AUTH=true disables authentication entirely. Only use for development with MCP Inspector (which has a known bug that prevents header forwarding).

Regional Endpoints

Region	Base URL
US-1	https://api.crowdstrike.com
US-2	https://api.us-2.crowdstrike.com
EU-1	https://api.eu-1.crowdstrike.com

Default Repository

The repository parameter is optional in all tools. When omitted, the server uses NGSIEM_DEFAULT_REPOSITORY from .env.

Benefits:

• Fewer parameters required
• Reduced client complexity
• Consistent repository usage

Override: Specify repository parameter to use a different repository for specific searches.

Repository Configuration

Define available repositories in config/repositories.yaml.

repositories:
  - name: base_sensor
    default: true
    description: "Main event stream"
  - name: zscaler
    description: "Zscaler Web logs"

Note: config/repositories.yaml is in .gitignore to prevent leaking sensitive internal names.

Logging

Log Levels

graph TD
    A[Log Entry] --> B{Level}
    B -->|DEBUG| C[API Responses<br/>Request Details]
    B -->|INFO| D[Operations<br/>Status Changes]
    B -->|WARNING| E[Recoverable Issues<br/>Timeouts]
    B -->|ERROR| F[Failures<br/>Exceptions]
    
    C --> G[Development]
    D --> H[Production]
    E --> H
    F --> H
    
    style D fill:#e8f5e9
    style E fill:#fff4e1
    style F fill:#ffebee

Log Location

• Default: ngsiem_mcp.log (current directory)
• Custom: Set LOG_FILE in .env

Debug Mode

# In .env
LOG_LEVEL=DEBUG

View logs:

tail -f ngsiem-mcp-http.log
tail -f ngsiem-mcp-app.log

Resources

• Model Context Protocol
• CrowdStrike NGSIEM API Documentation
• FalconPy SDK
• NGSIEM Query Language Guide

Contributing

For issues or enhancements:

1. Test changes locally
2. Update documentation
3. Follow existing code style
4. Ensure security best practices

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Built with: Python 3.13 | MCP SDK 1.25.0 | FalconPy 1.5.5 | Pydantic 2.12.5 by Rodkinal and GenIA