thunderclient-mcp
Enables AI tools to create and manage API requests and collections in Thunder Client, with automated collection and folder creation.
README
<p align="center"> <img src="https://github.com/thunderclient/thunder-client-support/blob/21d62c97dcc8168dc678b165fe678fd12c2f476b/images/thunder-icon.png" width="120" height="120" /> </p>
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
- Open Cline and navigate to the MCP Server section
- Click on Installed
- Click on Configure the MCP Server
- Add the following configuration inside the
mcpServersJSON:
{
"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.
For Continue.dev
- Add a new MCP server to your configuration
- Switch to Agent mode instead of Chat mode
- 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.
For GitHub Copilot
- Switch to Agent mode from Chat mode
- Click on the Tools icon in the interface
- Scroll down and click + Add more tools
- Select + Add MCP Server

- Choose Stdio as the connection type
- Enter the command to run as
npx thunderclient-mcp - Enter the mcp name
thunderclient-mcp-server-.... - Choose where to install MCP, select
GlobalorUser - 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
- Use Attach Context: Utilize the Attach Context option in your AI environment
- Attach Required Files: Include relevant files and specifically attach the
tc_createtool context - 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
projectDirparameter points to a valid Thunder Client workspace
Contributing
Feel free to contribute to this project by submitting issues or pull requests to improve functionality and compatibility with different AI development environments.
Audit
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
