The MCP Observer Server allows real-time monitoring of file system changes and notifies connected MCP clients when files are modified. This creates a bridge between your local file system and AI assistants, enabling them to respond automatically to file changes without manual intervention.
git clone https://github.com/username/mcp-observer-server.git
cd mcp-observer-server
uv pip install -r requirements.txt
touch src/mcp_observer_server/watched.txt
You can start the server using one of the following methods:
Using make:
make start
Or directly with npx:
npx @modelcontextprotocol/inspector uv run src/mcp_observer_server/server.py
The server provides two main ways to subscribe to file changes:
Path: /path/to/your/file.txt
The server provides a convenience tool to subscribe to the default watched file:
src/mcp_observer_server/watched.txt
.The server provides the following tools:
The MCP Observer Server can be used for various tasks:
If you don't see notifications:
The server uses a lightweight implementation built on:
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.
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"
]
}
}
}
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.
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.