MCP Playground

The MCP Playground is an interactive testing environment where you can test MCP servers, execute tools, chat with AI agents, and debug your agentic workflows—all in real-time before deploying to production.

Interactive Testing Environment

Test MCP tools, chat with agents, and debug workflows in real-time

Test

MCP Tools

Chat

With Agents

Debug

Workflows

Trace

Execution

What is the MCP Playground?

The MCP Playground provides three testing modes:

MCP Tool Testing

Execute individual MCP tools with custom parameters and see real-time results

Agent Chat Interface

Interact with AI agents in a conversational interface, test agent reasoning and tool usage

Workflow Testing

Test entire agentic workflows with input/output validation and execution tracing

Accessing the Playground

From MCP Server Management

Navigate to MCP Servers

Go to Agentic Toolkit → MCP Servers

Click on any MCP server to open its details, then click the Test in Playground button

From Agent Builder

Open Agent Playground

When editing an agent, click the Playground tab or button to test the agent with its configured MCP tools

From Workflow Editor

Test Workflow in Playground

In the workflow editor, use the Test button to open the Playground with the workflow's context and test execution

Playground Interface Overview

The Playground interface is divided into three main sections:

Main Interface Components

Sidebar (Left)

Browse and select MCP servers, view available tools, and see tool details

Main Panel (Center)

Chat interface for agents or tool testing interface with parameter inputs

Execution Drawer (Right/Bottom)

Real-time execution traces, step-by-step debugging, and performance metrics

MCP Playground Interface - Testing Tools and Chat with Agents

Testing MCP Tools

Individual Tool Testing

Test a single MCP tool with custom parameters:

Select MCP Server

In the left sidebar, choose the MCP server you want to test. All available tools from that server will be displayed.

Choose a Tool

Click on any tool from the list. The main panel will display the tool's parameters and input form.

Fill Parameters

Enter values for required and optional parameters. Parameter types are validated automatically:

Strings, numbers, booleans
Arrays and objects (JSON format)
File uploads (for tools that support files)

Execute Tool

Click Run Tool to execute. Results appear in real-time in the main panel and execution trace drawer.

📸 Screenshot #2 needed: Tool testing with parameters and results

Multi-Tool Testing

Test multiple tools in sequence or parallel:

Structured Testing Mode

Enable Structured Tests mode in the settings panel
Select multiple tools from the sidebar (checkbox selection)
Configure parameters for each selected tool
Execute all tools with a single click
View results side-by-side in the results panel

Chatting with AI Agents

Agent Chat Mode

Interact with AI agents that have access to MCP tools:

Switch to Agent Mode

Click the Agent tab in the Playground settings. Select the agent you want to test from the dropdown.

Start a Conversation

Type your message in the chat input. The agent will respond using its configured LLM and available MCP tools.

Example Prompts:

"Search for recent orders in the CRM"
"Get the weather forecast for New York"
"Analyze the sales data from last month"

Watch Agent Reasoning

As the agent processes your request, you'll see:

Thinking steps - Agent's reasoning process
Tool calls - Which MCP tools the agent invokes
Tool results - Data returned from each tool
Final response - Agent's synthesized answer

Review Execution Trace

Open the execution drawer to see detailed traces of every step, including LLM prompts, tool parameters, and timing information.

Agent Sessions

The Playground maintains conversation sessions:

Session Management

Create New Session - Start fresh conversation with the agent
Continue Session - Agent remembers previous messages
Session History - Access previous conversations
Session Context - View conversation context and memory

Testing Workflows

Workflow Mode

Test entire agentic workflows with inputs and outputs:

Select Workflow Mode

In Playground settings, switch to Workflow mode and select the workflow to test.

Configure Input Data

The Playground displays input fields based on the workflow's input schema. Fill in required and optional inputs.

Execute Workflow

Click Run Workflow. Watch real-time execution with streaming step updates.

Review Output

View workflow output, intermediate results from each node, and execution summary.

Execution Tracing

Real-Time Trace Viewer

The execution drawer shows detailed traces of every operation:

Trace Information

Execution Steps

Step-by-step execution flow
Timestamp for each operation
Step duration and performance
Success/failure indicators

Tool Execution Details

Tool name and parameters
Request payload (JSON)
Response data
Execution time

Agent Reasoning

LLM prompts sent
Agent thinking process
Tool selection reasoning
Token usage metrics

Error Details

Error messages and stack traces
Failed step identification
Retry attempts
Debugging hints

Streaming Updates

Watch execution in real-time with streaming updates:

Live Execution Streaming

See each step as it executes (no waiting for completion)
Monitor agent reasoning in real-time
Watch tool calls happen live
Identify performance bottlenecks immediately

Playground Settings

Configuration Options

Available Settings

Mode Selection

Choose between MCP Tool Testing, Agent Chat, or Workflow Testing modes

Server Selection

Select which MCP server(s) to use for testing

Agent Configuration

Choose agent, configure LLM settings, adjust temperature and max tokens

Chat/Form Toggle

Switch between conversational chat interface and structured form inputs

Tracing Options

Enable detailed execution traces, adjust verbosity level

Best Practices

Testing Best Practices

1. Test Tools Before Agent Integration

Always test individual MCP tools first to ensure they work correctly before adding them to agents.

2. Start with Simple Queries

When testing agents, begin with straightforward requests to verify basic functionality, then gradually increase complexity.

3. Review Execution Traces

Always check the execution trace to understand how the agent is using tools and making decisions.

4. Test Edge Cases

Verify behavior with invalid inputs, missing parameters, and error conditions before production deployment.

5. Monitor Performance

Use timing information in traces to identify slow tools or bottlenecks in your workflow.

6. Save Test Sessions

Keep agent conversation sessions as test cases for regression testing after making changes.

Debugging Common Issues

Troubleshooting Guide

Tool Execution Fails

Check authentication credentials are configured correctly
Verify parameter types match tool schema
Review execution trace for detailed error messages
Test the tool individually before using in agent

Agent Not Using Tools

Ensure MCP server is properly connected to the agent
Check tool descriptions are clear and relevant
Verify agent has permission to use the tools
Try more explicit prompts mentioning tool capabilities

Slow Execution

Check execution trace for slow tools
Verify MCP server is running and responsive
Review agent reasoning steps for unnecessary loops
Consider caching frequently accessed data

Incorrect Results

Review tool parameters passed by the agent
Check if tool output format matches expectations
Verify agent prompt includes necessary context
Test tool independently to isolate the issue