Filesystem Access MCP server for AI agents

This repository contains MCP (Model Context Protocol) servers designed for various use cases, integrated with CAMEL-AI. These servers enable different functionalities like filesystem access, SQL operations, and markdown processing to enhance AI interactions with different data sources.

Available MCP Servers

Filesystem Server

The Filesystem Server allows AI models to interact with the local filesystem, providing capabilities to read, write, and manipulate files and directories.

SQL Server

The SQL Server provides an interface for AI models to interact with SQL databases, enabling database queries and operations.

Markdown Servers

Two markdown-focused servers are available:

A note-taking application with markdown support
A document-to-markdown conversion utility

Installation Instructions

Prerequisites

Python 3.8 or higher
pip (Python package manager)

Setting Up the Environment

Clone the repository:

git clone https://github.com/parthshr370/MCP-Servers.git
cd MCP-Servers

Create and activate a virtual environment (recommended):

python -m venv venv

# On Windows
venv\Scripts\activate

# On macOS/Linux
source venv/bin/activate

Install dependencies:
```
pip install -r requirements.txt
```

Using the MCP Servers

Filesystem Server

Navigate to the filesystem server directory:
```
cd filesystem_server
```
Start the server:
```
python server.py
```
The server will be available for connection from CAMEL-AI or other compatible clients.

SQL Server

Navigate to the SQL server directory:
```
cd sql_server
```
Configure your database connection in the config file.
Start the server:
```
python sql_server.py
```
Connect to the server using a compatible client to perform SQL operations.

Markdown Servers

Document to Markdown Converter

Navigate to the markdown conversion directory:
```
cd markitdown_camel
```
Run the server:
```
python markdown_server.py
```
Use the API endpoints to convert documents to markdown format.

Note-taking Application

The Note-taking markdown server is in a separate repository:

Clone the repository:

git clone https://github.com/parthshr370/Md-Notes-Buddy.git
cd Md-Notes-Buddy

Follow the installation and usage instructions in that repository.

Connecting with CAMEL-AI

For each server, you can connect with CAMEL-AI by:

Starting the appropriate MCP server
Configuring CAMEL-AI to connect to the running server
Using the CAMEL-AI interface to interact with the specific functionality (files, SQL, or markdown)

The connection details and specific parameters will depend on which server you're using and your CAMEL-AI configuration.

How to add this MCP server to Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > MCP and click "Add new global MCP server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "cursor-rules-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "cursor-rules-mcp"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explictly ask the agent to use the tool by mentioning the tool name and describing what the function does.