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Overview

MCP Studio is your integrated development environment for creating Model Context Protocol (MCP) tools. Build custom tools that let AI assistants interact with your data and systems.

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Features

MCP Studio includes four main areas:

Tool Builder

Create and configure MCP tools with a visual editor.

Testing Playground

Test your tools before deploying to production.

Versions

Manage tool versions and rollbacks.

Git Integration

Connect to GitHub for version control.

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Tool Builder

The Tool Builder provides a visual interface for creating MCP tools:

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Creating a Tool

  1. Navigate to MCP Studio > Tool Builder
  2. Click New Tool
  3. Define tool properties:
    • Name: Unique identifier for the tool
    • Description: What the tool does (shown to AI)
    • Parameters: Input parameters the tool accepts
    • SQL Query: The query to execute

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Tool Parameters

Define parameters that AI assistants can pass to your tool: 
{
  "name": "customer_id",
  "type": "string",
  "description": "The unique customer identifier",
  "required": true
}

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Example Tool

name: get_customer_orders
description: Retrieve orders for a specific customer
parameters:
  - name: customer_id
    type: string
    required: true
  - name: limit
    type: integer
    default: 10
query: |
  SELECT * FROM orders
  WHERE customer_id = {{customer_id}}
  LIMIT {{limit}}

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Testing Playground

Test your tools before deploying:
  1. Go to MCP Studio > Testing Playground
  2. Select the tool to test
  3. Enter parameter values
  4. Click Run to execute
  5. Review the results
Test with edge cases and invalid inputs to ensure your tools handle errors gracefully.

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Version Management

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Creating Versions

  1. Go to MCP Studio > Versions
  2. Click Create Version
  3. Add a version name and description
  4. Select which tools to include

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Rolling Back

If a new version has issues:
  1. Go to Versions
  2. Find the previous stable version
  3. Click Rollback to restore it

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Git Integration

Connect your MCP tools to GitHub for version control:

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Connecting GitHub

  1. Go to MCP Studio > Git
  2. Click Connect GitHub
  3. Authorize Plumi to access your repositories
  4. Select or create a repository for your tools

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Syncing Tools

  • Push: Save your tools to GitHub
  • Pull: Load tools from GitHub
  • Commit History: View changes over time

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Best Practices

Write clear descriptions: AI assistants use tool descriptions to decide when to use each tool.
Validate inputs: Add parameter validation to prevent SQL injection and invalid queries.
Test thoroughly: Use the playground to test all parameter combinations before deploying.

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Using Your Tools

Once published, your tools are available via MCP: 
{
  "mcpServers": {
    "plumi": {
      "url": "https://your-workspace.plumi.ai/sse?api_key=YOUR_KEY"
    }
  }
}
AI assistants can then use your custom tools alongside built-in Plumi tools.