splunk/splunk-mcp-server2

Splunk MCP Server

A Model Context Protocol (MCP) server that enables AI assistants to securely search, analyze, and validate Splunk queries with built-in safety guardrails.

Overview

The Splunk MCP Server provides a standardized interface for AI assistants (like Claude, GitHub Copilot, etc.) to interact with Splunk Enterprise or Splunk Cloud. It implements the Model Context Protocol, allowing seamless integration between AI tools and your Splunk data.

Key Features

• Smart Search Integration: Execute SPL queries with multiple output formats (JSON, Markdown, CSV, Summary)
• Built-in Safety Guardrails: Automatic validation to prevent destructive or resource-intensive queries
• Data Protection: Automatic sanitization of sensitive data (credit cards, SSNs)
• Dual Transport Support: Both SSE (Server-Sent Events) and stdio transports
• Rich Splunk Features: Access indexes, saved searches, and execute complex queries
• Docker Ready: Containerized deployment options for both implementations

What is MCP?

The Model Context Protocol (MCP) is an open standard that enables seamless integration between AI assistants and external data sources. It provides:

• Standardized Communication: A common protocol for AI assistants to interact with external tools
• Security: Built-in authentication and authorization mechanisms
• Flexibility: Support for various transport mechanisms (stdio, SSE, WebSocket)
• Tool Discovery: Assistants can discover available tools and their capabilities

Available Implementations

This project provides two feature-complete implementations:

• Built with FastMCP framework for simplified development
• Async/await architecture for efficient performance
• Includes comprehensive test suite and interactive tools
• Docker support with management scripts

• Full type safety with TypeScript
• Built on the official MCP SDK
• Compatible with Node.js 18+
• Production-ready with compiled JavaScript output

Quick Start

Choose your preferred implementation:

Python Quick Start

cd python
cp .env.example .env
# Edit .env with your Splunk credentials
pip install -e .
python server.py

TypeScript Quick Start

cd typescript
cp .env.example .env
# Edit .env with your Splunk credentials
npm install
npm start

Core Capabilities

Available Tools

1. validate_spl - Validate SPL queries for risks before execution
2. search_oneshot - Execute blocking searches with immediate results
3. search_export - Stream large result sets efficiently
4. get_indexes - List available Splunk indexes with metadata
5. get_saved_searches - Access saved search configurations
6. run_saved_search - Execute pre-configured saved searches
7. get_config - Retrieve server configuration

Safety Features

The server includes intelligent guardrails to protect your Splunk environment:

• Risk Scoring: Queries are analyzed and assigned risk scores (0-100)
• Configurable Thresholds: Set your own risk tolerance levels
• Query Blocking: Dangerous queries are blocked before execution
• Performance Protection: Detects resource-intensive patterns
• Audit Trail: All queries are validated and logged

Supported Clients

• Claude Desktop
• Claude Code
• VS Code Copilot
• Any MCP-compatible client

Architecture

Both implementations follow the same architecture:

┌─────────────┐     MCP Protocol    ┌─────────────┐     REST API    ┌──────────┐
│ AI Assistant│ ◄─────────────────► │ MCP Server  │ ◄─────────────► │  Splunk  │
│  (Client)   │    stdio/SSE/WS     │ (This Repo) │    Port 8089   │ Instance │
└─────────────┘                     └─────────────┘                 └──────────┘

Security Considerations

• Credentials: Store securely in .env files (never commit to version control)
• Network: Use SSL/TLS for production deployments
• Permissions: Apply principle of least privilege for Splunk accounts
• Validation: All queries are validated before execution
• Sanitization: Sensitive data is automatically masked in outputs

Project Structure

splunk-mcp-server/
├── README.md           # This file
├── LICENSE             # MIT License
├── python/             # Python implementation
│   ├── README.md       # Detailed Python documentation
│   ├── server.py       # Main server implementation
│   ├── guardrails.py   # Query validation logic
│   └── tests/          # Test suite and tools
└── typescript/         # TypeScript implementation
    ├── README.md       # Detailed TypeScript documentation
    ├── server.ts       # Main server implementation
    ├── guardrails.ts   # Query validation logic
    └── tests/          # Test scripts

Contributing

We welcome contributions! Please see the implementation-specific README files for development setup and guidelines.

License

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

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• MCP Documentation: modelcontextprotocol.io
• Splunk REST API: Splunk Documentation

Choose your preferred implementation above to get started with detailed setup instructions, configuration options, and usage examples.