Stop Wasting Tokens: How MCP Servers Fix Context Window Problems

AIQAHacks — Sun, 29 Mar 2026 17:34:23 +0000

Introduction

Every time you paste Jira tickets, GitHub code, or DB data into AI tools like Claude or Cursor…

You’re wasting tokens.
And increasing cost without realizing it.

This is where MCP (Model Context Protocol) servers become a game changer.

What is MCP?

MCP (Model Context Protocol) allows LLMs to:

Fetch data dynamically from external systems
Avoid pasting large context manually
Use tools like APIs instead of raw text

Think of MCP as a smart data bridge, not a prompt dump.

Problem Without MCP

Traditional Approach

You paste everything into prompt:

Here is Jira ticket…
Here is GitHub code…
Here is database response…

Result:

Huge token usage
Slow responses
Context overflow
Repetition in every prompt

Solution: MCP-Based Approach

Instead of pasting data, you configure MCP servers.

👉 LLM fetches only what is needed
👉 Reduces token usage significantly
👉 Improves efficiency

MCP Configuration Examples (mcp.json)

Below are simplified examples you can use.

1. Atlassian (Jira) MCP Server
Tool for Jira integration using Atlassian Rovo ecosystem.

{
  "servers": {
    "jira": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-atlassian"],
      "env": {
        "ATLASSIAN_BASE_URL": "https://your-domain.atlassian.net",
        "ATLASSIAN_EMAIL": "your-email",
        "ATLASSIAN_API_TOKEN": "your-token"
      }
    }
  }
}

Usage Prompt: Fetch Jira ticket QA-123 and summarize acceptance criteria

👉 No need to paste ticket → saves tokens

2. GitHub MCP Server
Integrate code access using GitHub.

{
  "servers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_TOKEN": "your-token"
      }
    }
  }
}

Usage Prompt: Analyze login functionality in repo xyz and suggest test cases

👉 LLM fetches code directly → no copy-paste needed

3. MongoDB MCP Server
Access database dynamically using MongoDB.

{
  "servers": {
    "mongodb": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-mongodb"],
      "env": {
        "MONGODB_URI": "mongodb+srv://user:password@cluster.mongodb.net"
      }
    }
  }
}

Usage Prompt: Fetch last 5 failed transactions and analyze issues

👉 No raw DB dump required → huge token savings

Why MCP is Powerful for QA Engineers

Using MCP, QA engineers can:

Validate live data instead of static input
Automate end-to-end AI-assisted testing
Reduce prompt size drastically
Improve accuracy of AI responses

Conclusion

For QA engineers working with GenAI tools, MCP is not optional anymore — it’s essential for efficient and production-ready AI systems.

Automating Linkedℹ️n Messages✉️ with LinkBot🤖

AIQAHacks — Sun, 06 Oct 2024 07:35:47 +0000

Getting bored 🥱 building the same old automation projects like login forms and basic workflows❓

It's time to level up🚀 and create an innovative and easy project using selenium and python.

Project Overview 📒

In this article we will discuss how to build an LinkedIn Message Automation Tool or script that automates the process of sending messages to multiple users, all with in just a few lines of Python code using Selenium Webdriver.

Description🗒️

LinkBot 🤖 is a Selenium-Python based project that allows to automate tedious task of sending same messages to multiple user on LinkedIn. With a simple input of login credentials and profile URLs 🔗, the bot will do the rest, saving your time and effort.

Tech Stack

Before Getting Started, here's what you'll need:

Selenium 🌐: To interact with the browser and perform automated tasks.
Python 🐍: To write automation script.

📦Setting Up the Project

First, ensure that you have following Python libraries installed, if not then install using below command in cmd.

pip install selenium

🎯Getting Started with the code

The LinkBot script automates three tasks, so we can divided the code into three functions for the following:

login(): function logs into LinkedIn using credentials.
send_message(): navigate to user profile and send messages.
main(): contains username, password, list of users profile and a personalized message to be send.

1. Login Process

This method allows to login into LinkedIn by navigating to LinkedIn login page and entering your credentials and submitting the login form. We use Selenium's **WebDriverWait **to ensure elements are located before interacting with them.

def login(self):
    self.bot.get('https://www.linkedin.com/login')

    username_field = WebDriverWait(self.bot, 10).until(EC.presence_of_element_located((By.ID, 'username')))
    username_field.send_keys(self.username)

    password_field = WebDriverWait(self.bot, 10).until(EC.presence_of_element_located((By.ID, 'password')))
    password_field.send_keys(self.password)
    password_field.send_keys(Keys.RETURN)

    time.sleep(5)
    self.send_message()

2. Send Messages

The send_message() method sends the message to each profile URL. For every user it does the following:

Opens the user's profile.
Waits for the message button to become clickable.
Types the message in message box and sends it.

def send_message(self):
    for user in self.users:
        self.bot.get(user)
        try:
            message_btn = WebDriverWait(self.bot, 10).until(EC.element_to_be_clickable((By.XPATH, '//*[@id="profile-content"]/div/div[2]/div/div/main/section[1]/div[2]/div[3]/div/div[1]')))
            message_btn.click()

            message_box = WebDriverWait(self.bot, 10).until(EC.presence_of_element_located((By.CSS_SELECTOR, 'div.msg-form__contenteditable')))
            message_box.send_keys(Keys.BACKSPACE)
            message_box.send_keys(self.message)

            send_btn = WebDriverWait(self.bot, 10).until(EC.element_to_be_clickable((By.CSS_SELECTOR, 'button.msg-form__send-button')))
            send_btn.click()

            print(f'Message successfully sent to {user}')
        except Exception as e:
            print(f'Failed to send message to {user}: {str(e)}')

3. The Main Function

In the main function, you simply provide your LinkedIn credentials, the list of user's profile, and the message you want to send.

def main():
    username = 'abc@gmail.com'
    password = 'abc@123'
    users = ['https://www.linkedin.com/in/user-1', 'https://www.linkedin.com/in/user-2']
    message = 'Hi there! 👋 How are you? Hope you’re doing well. This is a test message sent by LinkBot 🤖'
    bot = LinkedInBot(username, password, users, message)

🚀How to run the Project❓

To start automating your LinkedIn messages with LinkBot, follow these steps:

Cloning the repository

git clone https://github.com/Manas15-coder/LinkedIn_Message_Automation

Install the dependencies

pip install selenium

Run the script

python linkbot.py

⭐GitHub Repository

Check out the full project on GitHub.If you find this project useful 😊, pls don't forget to give it a star ⭐on GitHub!

Manas15-coder / LinkedIn_Message_Automation

LinkBot 🤖, Linked In Message Automation bot, built using Selenium and Python. Using this automation script, same message ✉️ can be send to multiple users 👦, just need to input the user profile url 🔗, and in this way tedious task of sending messages to individuals can be automated 💻.

🔐 LinkBot 🤖: LinkedIn Message Automation

Automating linkedIn messages, so that same message ✉️ can be send to multiple users 👦, just need to input the user profile url 🔗, and in this way tedious task of sending messages to individuals can be automated 💻.

🚀 Tech Stack

Python 🐍
Selenium WebDriver 🌐

View on GitHub

DEV Community: AIQAHacks