Splunk MCP Server

A Model Context Protocol (MCP) server for interacting with Splunk Enterprise and Splunk Cloud. This server enables AI assistants to search Splunk data, list indexes, manage saved searches, and retrieve server information through a standardized interface.

Features

• Search Execution: Run SPL (Search Processing Language) queries with configurable time ranges and limits

• Index Management: List and filter available Splunk indexes

• Saved Searches: Retrieve and manage saved searches

• Application Listing: Browse installed Splunk applications

• Server Information: Get Splunk server details and health status

• Flexible Authentication: Support for both token-based and username/password authentication

• Async Operations: Built with modern Python async/await patterns

• Type Safety: Full Pydantic models for request/response validation

Related MCP server: splunk-mcp

Installation

Prerequisites

• Python 3.8 or higher

• Access to a Splunk Enterprise or Splunk Cloud instance

• Valid Splunk credentials (token or username/password)

Quick Start

1. Clone the repository:

   git clone https://github.com/yourusername/splunk-mcp.git
   cd splunk-mcp

2. Install dependencies:

   pip install -r requirements.txt

3. Configure environment variables:

   cp .env.example .env
   # Edit .env with your Splunk connection details

4. Run the server:

   python src/main.py

Development Installation

For development with additional tools:

pip install -e ".[dev]"

Configuration

The server is configured using environment variables. Copy .env.example to .env and configure:

Required Variables

# Splunk server connection
SPLUNK_HOST=your-splunk-server.com

Authentication (choose one method)

Token-based authentication (recommended):

SPLUNK_TOKEN=your-splunk-token-here

Username/password authentication:

SPLUNK_USERNAME=your-username
SPLUNK_PASSWORD=your-password

Optional Variables

SPLUNK_PORT=8089                    # Management port (default: 8089)
SPLUNK_SCHEME=https                 # http or https (default: https)
SPLUNK_VERIFY_SSL=true             # SSL verification (default: true)
SPLUNK_TIMEOUT=30                  # Request timeout (default: 30)
LOG_LEVEL=INFO                     # Logging level

Usage

Once running, the MCP server provides the following tools:

1. Search Splunk Data

Execute SPL queries with configurable parameters:

{
    "query": "search index=main error | head 10",
    "earliest_time": "-24h@h",
    "latest_time": "now",
    "max_count": 100,
    "timeout": 60
}

2. List Indexes

Get available Splunk indexes with optional filtering:

{
    "pattern": "main*"  # Optional pattern filter
}

3. Manage Saved Searches

Retrieve saved searches by name or owner:

{
    "search_name": "Security Alert",  # Optional
    "owner": "admin"                  # Optional
}

4. List Applications

Browse installed Splunk apps:

{
    "visible_only": true  # Show only visible apps
}

5. Get Server Information

Retrieve Splunk server details and health status.

API Reference

Search Parameters

Time Range Examples

• "-24h@h" - 24 hours ago, rounded to the hour

• "-7d@d" - 7 days ago, rounded to the day

• "2024-01-01T00:00:00" - Absolute timestamp

• "now" - Current time

• "-1h" - 1 hour ago

SPL Query Examples

# Basic search
search index=main error

# Search with stats
index=main | stats count by host

# Time-based search
index=security earliest=-1h | where _time > relative_time(now(), "-30m")

# Complex search with transformations
index=web_logs 
| rex field=_raw "(?<status_code>\d{3})" 
| stats count by status_code 
| sort -count

Authentication

Token-Based Authentication (Recommended)

1. Create a token in Splunk Web:

   • Go to Settings > Tokens

   • Click "New Token"

   • Set appropriate permissions

   • Copy the generated token

2. Configure environment:

   SPLUNK_TOKEN=your-token-here

Username/Password Authentication

SPLUNK_USERNAME=your-username
SPLUNK_PASSWORD=your-password

Note: Token authentication is more secure and is the recommended approach for production deployments.

Error Handling

The server provides detailed error responses:

{
    "status": "error",
    "error": "Authentication failed",
    "details": {
        "code": 401,
        "message": "Invalid credentials"
    }
}

Common error scenarios:

• Authentication failures: Invalid credentials or expired tokens

• Query syntax errors: Malformed SPL queries

• Permission issues: Insufficient access to indexes or searches

• Timeout errors: Long-running searches exceeding timeout limits

• Connection issues: Network problems or Splunk server unavailability

Security Considerations

• Use HTTPS: Always use encrypted connections in production

• Secure credentials: Store tokens and passwords securely

• Limit permissions: Use principle of least privilege for Splunk accounts

• Network security: Restrict network access to Splunk management ports

• Token rotation: Regularly rotate authentication tokens

Development

Project Structure

splunk-mcp/
├── src/
│   ├── main.py              # MCP server entry point
│   ├── splunk_client.py     # Splunk REST API client
│   ├── config.py            # Configuration management
│   └── models.py            # Pydantic data models
├── tests/                   # Test files
├── docs/                    # Documentation
└── requirements.txt         # Dependencies

Running Tests

pytest tests/

Code Formatting

black src/ tests/
isort src/ tests/

Type Checking

mypy src/

Deployment

Docker Deployment

Create a Dockerfile:

FROM python:3.11-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt

COPY src/ ./src/
COPY .env .

CMD ["python", "src/main.py"]

Build and run:

docker build -t splunk-mcp .
docker run --env-file .env splunk-mcp

Production Considerations

• Use a process manager like supervisor or systemd

• Configure proper logging and monitoring

• Set up health checks

• Use environment-specific configuration

• Implement proper secret management

Troubleshooting

Common Issues

1. Connection refused:

   • Check Splunk server is running

   • Verify host and port settings

   • Check network connectivity

2. Authentication errors:

   • Verify credentials are correct

   • Check token hasn't expired

   • Ensure user has necessary permissions

3. Search timeouts:

   • Reduce search time range

   • Optimize SPL query

   • Increase timeout setting

4. SSL errors:

   • Check certificate validity

   • Set SPLUNK_VERIFY_SSL=false for testing (not recommended for production)

Enabling Debug Logging

LOG_LEVEL=DEBUG python src/main.py

Contributing

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Add tests

5. Run the test suite

6. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• Issues: GitHub Issues

• Documentation: Project Wiki

• Splunk Documentation: Splunk REST API Reference

Changelog

v1.0.0

• Initial release

• Basic search functionality

• Token and username/password authentication

• Index and saved search management

• Application listing

• Server information retrieval