About quran_cloud_mcp_server
quran_cloud_mcp_server connects LLMs to the Quran Cloud API so they can retrieve relevant Quran text instead of relying on generated text. It is intended for users building Quran-related LLM workflows where exact wording matters.
Key features
- 01Retrieves Quran text from Quran Cloud API
- 02Fetches only requested content
- 03Designed to reduce text hallucinations
Use cases
- 01Look up Quran passages during an LLM conversation
- 02Provide exact Quran text for sensitive queries
MCP support
The MCP server exposes Quran Cloud API access to MCP clients, allowing LLMs to retrieve requested Quran data.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEquran_cloud_mcp_server
MCP server to help LLMs to get access to Quran API (https://alquran.cloud/api) to prevent the hallucination with Quran text.
hallucination is a big problem specially when you are working on sensitive data that each character is important.
one way of reducing the hallucination is by providing the context to your LLM but of course with large chunk of text like the holy Quran it's not efficient if you put all text in each request.
So, in this repo I have created an MCP server that's connect your LLM to a free API https://alquran.cloud/api that enables your model to retrieve only the data he needs.
Also, I will show to you how we can connect this MCP server to Claude desktop application.
Example of Claude the original response

Example of Claude the new response after connecting to Search-Quran MCP server

Installation
make sure you have python 3.13 & pip
Open your terminal and write these commands
Cloning
git clone https://github.com/marwanWaly/quran_cloud_mcp_server.git
Move to project directory
cd quran_cloud_mcp_server
Create virtual environment
python -m venv .venv
Activate venv
On Windows
.\venv\Scripts\activate
On Mac or linux
source .venv/bin/activate
Python packages installation
Use the package manager pip to install requirements.txt.
pip install -r requirements.txt
Create .env file
OPENAI_API_KEY=Your-secret-key
Run in terminal
python client.py
now you can directly chat with GPT4o in your terminal
Connect the server to Claude Desktop
Download Claude desktop and open it
Step 1
Select setting from the file menu

Step 2
Click on Developer then Edit Config

Step 3
Open claude_desktop_config.json

Step 4
Write this configuration in the file
{
"mcpServers": {
"Search-Quran": {
"command": "python",
"args": [
"PROJECT_PATH_ON_YOUR_PC\\server.py"
],
"host": "127.0.0.1",
"port": 8080,
"timeout": 30000
}
}
}
Don't forget to replace PROJECT_PATH_ON_YOUR_PC with the absolute path to your project server

Step 5
Restart Claude app (make sure it's completely closed from your taskbar by right click on Claude icon and select Quit)
Check if the new MCP has been added

Click on tools icon

Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.