Thunder Client MCP Server

The Thunder Client MCP server enables customers to integrate with AI tools to create requests and collections. It is compatible with various AI development environments, including Cline, Continue.dev, and GitHub Copilot.

Requirements

• A Business or Enterprise plan subscription is required to use the Thunder Client MCP Server.
• View Thunder Client pricing plans here.

Available Tools

This MCP server provides three powerful tools for managing Thunder Client operations:

1. tc_create

Description:
Saves API endpoints to Thunder Client, automatically creating collections and folders if they do not already exist.

Usage:

• Use AI to analyze your current project and automatically generate API requests in Thunder Client, with the appropriate collection and folder created as needed.
• Add new requests to a specific collection in Thunder Client.
• Dynamically create a request using an AI-generated prompt.

2. tc_debug

Description: Show Thunder Client CLI debug information using tc --debug in the given project directory.

• Usage: Troubleshoot and get detailed debug information from Thunder Client

Configuration for Different Environments

For Cline

1. Open Cline and navigate to the MCP Server section
2. Click on Installed
3. Click on Configure the MCP Server
4. Add the following configuration inside the mcpServers JSON:

{
  "mcpServers": {
    "thunderclient": {
      "name": "Thunder Client MCP Server",
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "thunderclient-mcp"]
    }
  }
}

Important: Replace thunderclient-mcp with /path/to/thunder-mcp/dist/index.js with your actual index.js location in local Dev mode.

Once configured, you can use all tc_* command tools in Cline's MCP interface.

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For Continue.dev

1. Add a new MCP server to your configuration
2. Switch to Agent mode instead of Chat mode
3. Configure using the following YAML structure:

name: Thunder Client MCP Server
version: 0.0.1
schema: v1
mcpServers:
  - name: Thunder Client MCP Server
    command: npx
    args:
      - thunderclient-mcp

Important: Replace thunderclient-mcp with /path/to/thunder-mcp/dist/index.js with your actual index.js location in local Dev mode.

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For GitHub Copilot

1. Switch to Agent mode from Chat mode
2. Click on the Tools icon in the interface
3. Scroll down and click + Add more tools
4. Select + Add MCP Server
5. Choose Stdio as the connection type
6. Enter the command to run as npx thunderclient-mcp
7. Enter the mcp name thunderclient-mcp-server-....
8. Choose where to install MCP, select Global or User
9. Save the configuration

Important: Replace npx thunderclient-mcp with node /path/to/thunder-mcp/dist/index.js with your actual index.js location in local Dev mode.

Example Prompts

This document contains simple example prompts for the tc_create tool to extract APIs from code files and save them to Thunder Client.

Extract APIs from Code Files

1. Extract APIs from Current Project

"Get the endpoints from the current project and save them with collection name 'My API' using Thunder Client MCP."

2. Extract APIs from Files and Folders

"Get the endpoints from app/main.py and save them with collection name 'E-commerce API' and folder name 'Products' using Thunder Client MCP."

"Get the endpoints from the src/routes/ folder and save them with collection name 'Node API' using Thunder Client MCP."

3. Create Simple HTTP Requests

"Create a POST request to https://api.example.com/users with a JSON body and an Authorization header using Thunder Client MCP."

Running Locally

npm i
npm run build

After building, a dist folder will be created. Copy the index.js path from the dist folder - this path will be used in your MCP server configuration.

Troubleshooting

If the Agent Is Not Executing Commands Properly

1. Use Attach Context: Utilize the Attach Context option in your AI environment
2. Attach Required Files: Include relevant files and specifically attach the tc_create tool context
3. Provide Clear Prompts: Give detailed, specific prompts to assist with command execution

Common Issues

• Path Issues: Ensure all file paths are absolute and correctly formatted for your operating system
• Node.js Version: Verify you're using a compatible Node.js version
• Permissions: Check that the MCP server has appropriate file system permissions
• Project Directory: Ensure the projectDir parameter points to a valid Thunder Client workspace

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Contributing

Feel free to contribute to this project by submitting issues or pull requests to improve functionality and compatibility with different AI development environments.