Splunk Agent Observability MCP Server

The Splunk Agent Observability Model Context Protocol (MCP) server enables seamless integration between AI-powered IDEs, such as Cursor, or VS Code with GitHub Copilot, and Splunk Agent Observability’s evaluation and observability platform. With MCP, you can access Splunk Agent Observability’s capabilities directly from your development environment, including:

Creating and managing datasets
Running experiments
Setting up prompt templates
Getting signals on Agent Streams
Integrating Splunk Agent Observability with your code

Prerequisites

Before you begin, ensure you have the following:

AI-enabled IDE

Install an AI-enabled IDE such as Cursor or VS Code with AI capabilities

API key

Generate your Splunk Agent Observability API key from the API keys page in the UI.

Configure your IDE

The Splunk Agent Observability MCP server works with both Cursor and VS Code. Follow the steps below for your IDE:

VS Code
Cursor

Install GitHub Copilot

Install the GitHub Copilot extension if you haven’t already

Open MCP settings

Open the Command Palette (Ctrl + Shift + P on Windows/Linux, or Cmd + Shift + P on Mac) and search for “MCP: Open User Configuration”

Add the Splunk Agent Observability MCP server configuration

Copy and paste the configuration below. Replace YOUR-API-KEY with your actual Splunk Agent Observability API key.

VSCode MCP Configuration

{
  "servers": {
    "splunk_ao_mcp_server": {
      "url": "<your-splunk-ao-api-url>/mcp/http/mcp",
      "headers": {
        "Splunk-AO-API-Key": "YOUR-API-KEY",
        "Accept": "text/event-stream"
      }
    }
  },
  "inputs": []
}

If you’re using a self-hosted Splunk Agent Observability deployment, replace the <your-splunk-ao-api-url>/mcp/http/mcp url with your deployment URL. The format of this URL is based on your URL, replacing console with api and appending /mcp/http/mcp.

Reload VS Code

Reload VS Code by opening the Command Palette and running “Developer: Reload Window” for the changes to take effect

Open the Tools & MCP settings

Open the Cursor command palette (Ctrl + Shift + P on Windows/Linux, or Cmd + Shift + P on Mac), then choose “Open MCP Settings”.

Open the MCP server configuration file

Click on Add Custom MCP to open the mcp.json MCP configuration file, or New MCP Server if you already have other MCP servers configured.

Add the Splunk Agent Observability MCP server configuration

Copy and paste the configuration below. Replace YOUR-API-KEY with your actual Splunk Agent Observability API key.

Cursor MCP Configuration

{
  "mcpServers": {
    "splunk_ao_mcp_server": {
      "url": "<your-splunk-ao-api-url>/mcp/http/mcp",
      "headers": {
        "Splunk-AO-API-Key": "YOUR-API-KEY",
        "Accept": "text/event-stream"
      }
    }
  }
}

Save and restart

Save the configuration and restart Cursor for the changes to take effect

The configuration is the same for both Cursor and VS Code. Make sure to replace YOUR-API-KEY with your actual Splunk Agent Observability API key from the API keys page in the UI.

Verify your setup

Once configured, you can verify your MCP setup by asking your AI assistant in your IDE:

Can you show me how to add Splunk Agent Observability logging to my agent bot?

Help me create a synthetic dataset for customer support queries

How do I integrate Splunk Agent Observability with LangChain?

Your AI assistant should now be able to access Splunk Agent Observability’s capabilities and respond with information from your Splunk Agent Observability account.

Tools

The Splunk Agent Observability MCP server provides powerful tools that you can access through natural conversation with your AI assistant. Simply ask questions or make requests, and the AI will use these tools to help you.

Create Datasets

Generate synthetic datasets or upload your own data to test and evaluate your AI applications. The tool supports creating datasets with various types of queries including general queries, prompt injections, off-topic content, and toxic content scenarios.What you can ask:

Create a dataset with 50 customer service queries about billing issues

Generate a dataset of 30 chatbot queries, including some prompt injection attempts

Make a dataset with product recommendation queries and include off-topic questions

Check Dataset Status

Track the progress of your dataset generation and preview the generated content. You’ll see the first 10 rows of data along with generation status and progress updates.What you can ask:

Check the status of my dataset that's currently generating

Show me the preview of dataset abc-123

Is my customer service dataset ready yet?

Create Prompt Templates

Build reusable prompt templates that you can use across all your projects. Set up model configurations, temperature settings, and other parameters for consistent prompt behavior.What you can ask:

Create a prompt template called "Friendly Assistant" for customer support responses

Make a prompt template for summarizing technical documentation with lower temperature

Set up a chat template for a code review assistant

Set Up Experiments

Get complete guidance on setting up and running Splunk Agent Observability experiments, including dataset preparation, evaluators configuration, and integration with your existing code. Available for Python and other supported languages.What you can ask:

How do I set up a Splunk Agent Observability experiment in Python?

Show me how to run an experiment with my RAG application

Guide me through creating an experiment for my agentic workflow

Get Signals

Analyze your application’s Agent Streams to identify issues, patterns, and opportunities for improvement. Get specific recommendations based on your logged data.What you can ask:

What issues do you see in my production Agent Stream?

Fetch the most recent signals from Splunk Agent Observability and propose fixes for them in my code

Get insights about my chatbot Agent Stream and suggest improvements

Integrate with OpenAI

Get step-by-step integration guides for adding Splunk Agent Observability to your OpenAI applications. Automatically log prompts, responses, model parameters, and token usage with minimal code changes.What you can ask:

How do I add Splunk Agent Observability logging to my OpenAI application?

Show me how to integrate Splunk Agent Observability with OpenAI

Help me set up Splunk Agent Observability for my GPT-4 chatbot

Integrate with LangChain

Get complete integration instructions for adding Splunk Agent Observability to your LangChain applications. Capture full traces of your chains, agents, and tools with automatic logging.What you can ask:

How do I integrate Splunk Agent Observability with my LangChain application?

Show me how to add Splunk Agent Observability tracing to my LangChain agent

Help me log my LangChain RAG pipeline with Splunk Agent Observability

Search Documentation

Find relevant information, code examples, API references, and implementation guides across all Splunk Agent Observability documentation. Get direct links to the pages you need.What you can ask:

How do I set up data logging in Splunk Agent Observability?

Find documentation about custom evaluators

Search for examples of agentic AI evaluation

Example use cases

Create a synthetic dataset

Ask your AI assistant:

Create a synthetic dataset with 20 customer service queries about product
returns. Include both general queries and off-topic queries.

The MCP server will guide you through the dataset creation process and provide a dataset ID to track progress.

Get integration help

Ask your AI assistant:

How do I integrate Splunk Agent Observability with my LangChain application in Python?

The MCP server will provide complete integration code examples and setup instructions.

Get Signals

Ask your AI assistant:

Fetch the most recent signals from Splunk Agent Observability and propose fixes for them in my code

The MCP server will analyze your Agent Stream and suggest improvements.

Troubleshooting

Error connecting to Splunk Agent Observability MCP Server

Check that the MCP server URL is set to <your-splunk-ao-api-url>/mcp/http/mcp
Ensure the Accept header is set to text/event-stream
Restart your IDE MCP connection after making configuration changes

API key errors

Confirm your API key is properly set in the configuration
Check that your API key has not expired
Generate a new API key from the API keys page in the UI

Next steps

Log your first trace

Learn how to log your first trace with Splunk Agent Observability

Run your first experiment

Set up and run experiments to evaluate your AI applications

Explore integrations

Learn about Splunk Agent Observability integrations with third-party frameworks

Overview

Get Started

Observability

Evaluators

Signals

AI Assistant

Luna Studio

Experiments

Agent Control

Annotations

Integrations

Security

References

Prerequisites

Configure your IDE

Verify your setup

Tools

Example use cases

Create a synthetic dataset

Get integration help

Get Signals

Troubleshooting

Next steps

Log your first trace

Run your first experiment

Explore integrations

​Prerequisites

​Configure your IDE

​Verify your setup

​Tools

​Example use cases

​Create a synthetic dataset

​Get integration help

​Get Signals

​Troubleshooting

​Next steps

Log your first trace

Run your first experiment

Explore integrations

Prerequisites

Configure your IDE

Verify your setup

Tools

Example use cases

Create a synthetic dataset

Get integration help

Get Signals

Troubleshooting

Next steps