Dheepu2671999/NeoLoad-MCP-Server-and-Gemini

NeoLoad + Gemini integrated MCP client-server framework

Prerequisites

Need to make sure you have access to the Neoload Saas account using the api key generated from the application

Have nodejs, gemini cli[also install the extension in the vs code] , VS code installed in the system

Setup

1. Create a new Project directory and navigate to them

mkdir your_project_directory
cd your_project_directory

2. Create the python enviorment

python -m venv .venv

3. Install all the dependencis using the requirements.txt

pip install -r requirements.txt

4. If the above step doesnt install the dependencies make sure to install them manually

pip install neoload
pip install mcp
pip install streamlit
pip install python-dotenv
npm install -g @google/gemini-cli
pip install fastmcp
pip install pandas

5. In .env file place the token u recieved from the neoload saas

Usage

1. Start the MCP server using the command

python server.py

2. Start the MCP Client using the command

streamlit run client.py

3. In the VS code login into the gemini extension once the authentication is done make sure to enable the agent button present in the prompt box to recogonize the MCP server

4. Type /mcp in the prompt box to check if the tools are available for us

5. Like wise in terminal as well type

gemini 

To launch the gemini make sure it displays the mcp server is active

Note

• To use the gemini cli only server.py must be running.
• Dockerfile are present for both client and server which will just run the MCP workflow but not integrate with the gemini

Sample Prompts

• Authenticate the tool
• can u extract the details from the userpath [provide the userpath name] and transaction [provide the transaction name]
• Provide the Performance summary of the report extracted