Splunk MCP Server
Overview
Details
The Model Context Protocol (MCP) is an open standard and framework that enables seamless, secure, and standardized two-way communication between AI applications (like large language models) and external data sources or tools. It acts as a universal adapter allowing AI systems to access, execute, and integrate functionalities from diverse systems through a common protocol, simplifying data sharing and tool interoperability without custom coding for each integration.
Splunk's Model Context Protocol (MCP) server leverages this to provide a standardized, secure, and scalable interface to connect AI assistants, agents, and other intelligent systems with data in the Splunk platform for both Enterprise & Cloud customers in beta.
🔑 Key Features
- Universal Connectivity
Seamlessly connects AI agents and tools to Splunk data resources in a secure and efficient manner.
- Enterprise-Grade Security
Includes built-in authentication, authorization, and Role-Based Access Control (RBAC).
- Rapid Deployment
Offers a plug-and-play solution, eliminating the need for custom integrations.
⚙️ Core Capabilities
- Explore the Data
Navigate and interact with Splunk data effortlessly.
- Discover Knowledge Objects
Identify and access relevant saved searches, lookups, and other knowledge assets.
- Execute Searches
Run powerful Splunk queries to extract insights and drive intelligent workflows.
- Leverage AI capabilities from Splunk’s AI Assistant for SPL & MLTK
SPL search generation from natural language, search optimization, search explanation, retrieve MLTK models and algorithms.
MCP Server for Splunk Platform
The rise of agentic AI systems and Large Language Models (LLMs) has created a powerful new way to interact with complex data. However, securely and efficiently connecting these AI tools to data in the Splunk platform can be a challenge.
The Splunk Model Context Protocol (MCP) server for Splunk Enterprise and Splunk Cloud Platform can help resolve this challenge. It's a fully-managed service that acts as a secure bridge, allowing AI agents and applications to interact with your Splunk environment using a standardized protocol. This enables you to query your data, get information about your environment, and automate tasks using natural language—without needing to be an expert in Splunk Search Processing Language (SPL).
The MCP server exposes core Splunk functionality as "tools" that your AI agent can call. The tools that are currently available:
generate_spl: Generate SPL for a natural language query (new)optimize_spl: Optimize the given SPL (new)explain_spl: Explain the specified SPL in natural language (new)ask_splunk_question: Answer natural language questions about Splunk (new)run_splunk_query: Run a query and return the results. Use this to retrieve log data, perform aggregations, or search indexed data.get_splunk_info: Get basic information about your Splunk instance, such as version and server name.get_indexes: Get a list of the Splunk indexes that you have permission to access.get_index_info: Get detailed information about a specific Splunk index.get_metadata: Retrieve metadata (hosts, sources, or source types) for a given index to assist with query building.get_user_info: Get information about the current, authenticated user.get_knowledge_objects: Retrieve a list of knowledge objects of a specified type, such as saved searches, data models, macros, and more.
For more details, please refer to:
đź”— Leveraging Splunk MCP and AI for enhanced IT operations and security investigations