Splunk
Interact with Splunk Enterprise/Cloud using natural language queries.
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:
-
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
-
API Mode
- RESTful API endpoints
- Access via
/api/v1
endpoint prefix - Start with
python splunk_mcp.py api
-
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)
Quick Start with UV
-
Clone the repository:
git clone <repository-url> cd splunk-mcp
-
Install dependencies with UV:
# Install main dependencies uv sync # Or install with development dependencies uv sync --extra dev
-
Run the application:
# 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
# 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:
# Install dependencies
poetry install
# Run the application
poetry run python splunk_mcp.py
Using pip (Alternative)
# Install dependencies
pip install -r requirements.txt
# Run the application
python splunk_mcp.py
Operating Modes
The tool operates in three modes:
-
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
-
API Mode
- RESTful API endpoints
- Access via
/api/v1
endpoint prefix - Start with
python splunk_mcp.py api
-
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:
- SSE mode (default for MCP clients):
# 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
- STDIO mode:
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.
- SSE Mode (Default):
docker compose up -d mcp
- API Mode:
docker compose run --rm mcp python splunk_mcp.py api
- STDIO Mode:
docker compose run -i --rm mcp python splunk_mcp.py stdio
Testing with Docker
The project includes a dedicated test environment in Docker:
- Run all tests:
./run_tests.sh --docker
- Run specific test components:
# 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
- Building Images:
# Build both images
docker compose build
# Build specific service
docker compose build mcp
docker compose build test
- Viewing Logs:
# View all logs
docker compose logs
# Follow specific service logs
docker compose logs -f mcp
- Debugging:
# 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
- Environment Variables:
- Never commit
.env
files - Use
.env.example
as a template - Consider using Docker secrets for production
- SSL Verification:
VERIFY_SSL=true
recommended for production- Can be disabled for development/testing
- Configure through environment variables
- 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 addressSPLUNK_PORT
: Splunk management port (default: 8089)SPLUNK_USERNAME
: Your Splunk usernameSPLUNK_PASSWORD
: Your Splunk passwordSPLUNK_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:
- Default (Secure) Mode:
VERIFY_SSL=true
- Full SSL certificate verification
- Hostname verification enabled
- Recommended for production environments
- Relaxed Mode:
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:
poetry run pytest
With coverage reporting:
poetry run pytest --cov=splunk_mcp
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