# Splunk MCP (Model Context Protocol) Tool
A FastMCP-based tool for interacting with Splunk Enterprise/Cloud through natural language. This tool provides a set of capabilities for searching Splunk data, managing KV stores, and accessing Splunk resources through an intuitive interface.
## Operating Modes
The tool operates in three modes:
1. **SSE Mode** (Default)
- Server-Sent Events based communication
- Real-time bidirectional interaction
- Suitable for web-based MCP clients
- Default mode when no arguments provided
- Access via `/sse` endpoint
2. **API Mode**
- RESTful API endpoints
- Access via `/api/v1` endpoint prefix
- Start with `python splunk_mcp.py api`
3. **STDIO Mode**
- Standard input/output based communication
- Compatible with Claude Desktop and other MCP clients
- Ideal for direct integration with AI assistants
- Start with `python splunk_mcp.py stdio`
## Features
- **Splunk Search**: Execute Splunk searches with natural language queries
- **Index Management**: List and inspect Splunk indexes
- **User Management**: View and manage Splunk users
- **KV Store Operations**: Create, list, and manage KV store collections
- **Async Support**: Built with async/await patterns for better performance
- **Detailed Logging**: Comprehensive logging with emoji indicators for better visibility
- **SSL Configuration**: Flexible SSL verification options for different security requirements
- **Enhanced Debugging**: Detailed connection and error logging for troubleshooting
- **Comprehensive Testing**: Unit tests covering all major functionality
- **Error Handling**: Robust error handling with appropriate status codes
- **SSE Compliance**: Fully compliant with MCP SSE specification
## Available MCP Tools
The following tools are available via the MCP interface:
### Tools Management
- **list_tools**
- Lists all available MCP tools with their descriptions and parameters
### Health Check
- **health_check**
- Returns a list of available Splunk apps to verify connectivity
- **ping**
- Simple ping endpoint to verify MCP server is alive
### User Management
- **current_user**
- Returns information about the currently authenticated user
- **list_users**
- Returns a list of all users and their roles
### Index Management
- **list_indexes**
- Returns a list of all accessible Splunk indexes
- **get_index_info**
- Returns detailed information about a specific index
- Parameters: index_name (string)
- **indexes_and_sourcetypes**
- Returns a comprehensive list of indexes and their sourcetypes
### Search
- **search_splunk**
- Executes a Splunk search query
- Parameters:
- search_query (string): Splunk search string
- earliest_time (string, optional): Start time for search window
- latest_time (string, optional): End time for search window
- max_results (integer, optional): Maximum number of results to return
- **list_saved_searches**
- Returns a list of saved searches in the Splunk instance
### KV Store
- **list_kvstore_collections**
- Lists all KV store collections
- **create_kvstore_collection**
- Creates a new KV store collection
- Parameters: collection_name (string)
- **delete_kvstore_collection**
- Deletes an existing KV store collection
- Parameters: collection_name (string)
## SSE Endpoints
When running in SSE mode, the following endpoints are available:
- **/sse**: Returns SSE connection information in text/event-stream format
- Provides metadata about the SSE connection
- Includes URL for the messages endpoint
- Provides protocol and capability information
- **/sse/messages**: The main SSE stream endpoint
- Streams system events like heartbeats
- Maintains persistent connection
- Sends properly formatted SSE events
- **/sse/health**: Health check endpoint for SSE mode
- Returns status and version information in SSE format
## Error Handling
The MCP implementation includes consistent error handling:
- Invalid search commands or malformed requests
- Insufficient permissions
- Resource not found
- Invalid input validation
- Unexpected server errors
- Connection issues with Splunk server
All error responses include a detailed message explaining the error.
## Installation
### Using UV (Recommended)
UV is a fast Python package installer and resolver, written in Rust. It's significantly faster than pip and provides better dependency resolution.
#### Prerequisites
- Python 3.10 or higher
- UV installed (see [UV installation guide](https://docs.astral.sh/uv/getting-started/installation/))
#### Quick Start with UV
1. **Clone the repository:**
```bash
git clone <repository-url>
cd splunk-mcp
```
2. **Install dependencies with UV:**
```bash
# Install main dependencies
uv sync
# Or install with development dependencies
uv sync --extra dev
```
3. **Run the application:**
```bash
# SSE mode (default)
uv run python splunk_mcp.py
# STDIO mode
uv run python splunk_mcp.py stdio
# API mode
uv run python splunk_mcp.py api
```
#### UV Commands Reference
```bash
# Install dependencies
uv sync
# Install with development dependencies
uv sync --extra dev
# Run the application
uv run python splunk_mcp.py
# Run tests
uv run pytest
# Run with specific Python version
uv run --python 3.11 python splunk_mcp.py
# Add a new dependency
uv add fastapi
# Add a development dependency
uv add --dev pytest
# Update dependencies
uv sync --upgrade
# Generate requirements.txt
uv pip compile pyproject.toml -o requirements.txt
```
### Using Poetry (Alternative)
If you prefer Poetry, you can still use it:
```bash
# Install dependencies
poetry install
# Run the application
poetry run python splunk_mcp.py
```
### Using pip (Alternative)
```bash
# Install dependencies
pip install -r requirements.txt
# Run the application
python splunk_mcp.py
```
## Operating Modes
The tool operates in three modes:
1. **SSE Mode** (Default)
- Server-Sent Events based communication
- Real-time bidirectional interaction
- Suitable for web-based MCP clients
- Default mode when no arguments provided
- Access via `/sse` endpoint
2. **API Mode**
- RESTful API endpoints
- Access via `/api/v1` endpoint prefix
- Start with `python splunk_mcp.py api`
3. **STDIO Mode**
- Standard input/output based communication
- Compatible with Claude Desktop and other MCP clients
- Ideal for direct integration with AI assistants
- Start with `python splunk_mcp.py stdio`
## Usage
### Local Usage
The tool can run in three modes:
1. SSE mode (default for MCP clients):
```bash
# Start in SSE mode (default)
poetry run python splunk_mcp.py
# or explicitly:
poetry run python splunk_mcp.py sse
# Use uvicorn directly:
SERVER_MODE=api poetry run uvicorn splunk_mcp:app --host 0.0.0.0 --port 8000 --reload
```
3. STDIO mode:
```bash
poetry run python splunk_mcp.py stdio
```
### Docker Usage
The project supports both the new `docker compose` (V2) and legacy `docker-compose` (V1) commands. The examples below use V2 syntax, but both are supported.
1. SSE Mode (Default):
```bash
docker compose up -d mcp
```
2. API Mode:
```bash
docker compose run --rm mcp python splunk_mcp.py api
```
3. STDIO Mode:
```bash
docker compose run -i --rm mcp python splunk_mcp.py stdio
```
### Testing with Docker
The project includes a dedicated test environment in Docker:
1. Run all tests:
```bash
./run_tests.sh --docker
```
2. Run specific test components:
```bash
# Run only the MCP server
docker compose up -d mcp
# Run only the test container
docker compose up test
# Run both with test results
docker compose up --abort-on-container-exit
```
Test results will be available in the `./test-results` directory.
### Docker Development Tips
1. **Building Images**:
```bash
# Build both images
docker compose build
# Build specific service
docker compose build mcp
docker compose build test
```
2. **Viewing Logs**:
```bash
# View all logs
docker compose logs
# Follow specific service logs
docker compose logs -f mcp
```
3. **Debugging**:
```bash
# Run with debug mode
DEBUG=true docker compose up mcp
# Access container shell
docker compose exec mcp /bin/bash
```
Note: If you're using Docker Compose V1, replace `docker compose` with `docker-compose` in the above commands.
### Security Notes
1. **Environment Variables**:
- Never commit `.env` files
- Use `.env.example` as a template
- Consider using Docker secrets for production
2. **SSL Verification**:
- `VERIFY_SSL=true` recommended for production
- Can be disabled for development/testing
- Configure through environment variables
3. **Port Exposure**:
- Only expose necessary ports
- Use internal Docker network when possible
- Consider network security in production
## Environment Variables
Configure the following environment variables:
- `SPLUNK_HOST`: Your Splunk host address
- `SPLUNK_PORT`: Splunk management port (default: 8089)
- `SPLUNK_USERNAME`: Your Splunk username
- `SPLUNK_PASSWORD`: Your Splunk password
- `SPLUNK_TOKEN`: (Optional) Splunk authentication token. If set, this will be used instead of username/password.
- `SPLUNK_SCHEME`: Connection scheme (default: https)
- `VERIFY_SSL`: Enable/disable SSL verification (default: true)
- `FASTMCP_LOG_LEVEL`: Logging level (default: INFO)
- `SERVER_MODE`: Server mode (sse, api, stdio) when using uvicorn
### SSL Configuration
The tool provides flexible SSL verification options:
1. **Default (Secure) Mode**:
```env
VERIFY_SSL=true
```
- Full SSL certificate verification
- Hostname verification enabled
- Recommended for production environments
2. **Relaxed Mode**:
```env
VERIFY_SSL=false
```
- SSL certificate verification disabled
- Hostname verification disabled
- Useful for testing or self-signed certificates
## Testing
The project includes comprehensive test coverage using pytest and end-to-end testing with a custom MCP client:
### Running Tests
Basic test execution:
```bash
poetry run pytest
```
With coverage reporting:
```bash
poetry run pytest --cov=splunk_mcp
```