MCP s

This MCP server collection offers a set of specialized servers designed to support common use cases such as interacting with the filesystem, running SQL-related tasks, and working with Markdown notes. Each server is intended to be accessed via the MCP framework and integrated with CAMEL-AI workflows, enabling automated prompts, data extraction, transformation, and storage operations within your projects. Since the repository groups multiple server implementations, you can selectively enable the server(s) that match your current task (e.g., note-taking workflows with Markdown, querying or manipulating a database, or performing file-system operations).

To use these tools effectively, identify the server that aligns with your use case and follow the installation instructions. Once installed, you can invoke the server’s capabilities through your MCP client or CAMEL-AI integration, passing the appropriate prompts and data. The servers are designed to be composable, so you can chain results from one server into another to build end-to-end automation workflows such as extracting data from Markdown notes, storing structured results in a database, and reading back from the filesystem as needed.

Prerequisites

• Git and a supported runtime (Node.js for npm-based setup, Python for uv/uvx setups, or Docker for containerized usage).
• Access to the internet to fetch dependencies.

Option A: Clone the repository and install locally

1. git clone https://github.com/parthshr370/MCP-Servers.git
2. cd MCP-Servers
3. Follow the specific server READMEs for each subdirectory (filesystem_server, sql_server, markitdown_camel) to install dependencies and run the server. Each subproject typically includes its own setup steps (e.g., npm install, pip install, or docker build).

Option B: Use a containerized approach (if docker configurations are provided in the submodules)

1. Ensure Docker is installed and running.
2. Navigate to the desired server directory and follow its docker-related instructions (e.g., docker build and docker run commands) as described in the subproject README.

Option C: Run a specific server directly (if Node.js/uvx examples are provided)

• Node.js example (if available):
  • Ensure dependencies are installed: npm install
  • Run the server: npm start or node path/to/server.js
• Python example (uv/uvx-based):
  • Ensure dependencies are installed: pip install -r requirements.txt
  • Run the server per the subproject instructions (e.g., uvx path/to/server or python -m module_name)

Note: Because this repository aggregates multiple MCP servers, always refer to the individual server READMEs for exact installation commands, environment variables, and runtime details for that server.

Environment variables and configuration options may vary by server. Common considerations include:

• CAMEL-AI integration keys or endpoints if required by your deployment.
• Paths to data directories or databases used by the server (be mindful of permissions).
• Network ports and firewall rules if running in a shared environment.
• Any required authentication tokens or API keys for external services. If you encounter issues, check the server-specific README files under filesystem_server, sql_server, and markitdown_camel for troubleshooting steps and examples.