Feedly MCP server

This server implements the Model Context Protocol (MCP) for Feedly, allowing you to retrieve the latest entries from your Feedly categories and mark entries as read. It provides a simple way to interact with your Feedly account programmatically.

Installation

Install the feedly-mcp package using pip:

pip install feedly-mcp

Usage

Configuration

Before using the MCP server, you need to set up your Feedly API credentials:

1. Obtain your Feedly API access token from your Feedly account
2. Configure your environment with the token

Getting Latest Entries

To retrieve the latest entries from a specific category:

from feedly_mcp import FeedlyMCP

# Initialize the MCP client
client = FeedlyMCP(access_token="your_feedly_access_token")

# Get the latest entries from a category
entries = client.get_latest_entries(category_id="your_category_id", count=10)

# Process the entries
for entry in entries:
    print(entry.title)
    print(entry.url)

Marking Entries as Read

To mark an entry as read:

from feedly_mcp import FeedlyMCP

# Initialize the MCP client
client = FeedlyMCP(access_token="your_feedly_access_token")

# Mark a specific entry as read
client.mark_as_read(entry_id="entry_id_to_mark")

Typical Workflow

A common workflow with the Feedly MCP is:

1. Get the latest entries from a category
2. Check each entry based on your criteria
3. Mark uninteresting entries as read
4. Keep interesting entries unread for later review

Example implementation:

from feedly_mcp import FeedlyMCP

client = FeedlyMCP(access_token="your_feedly_access_token")
entries = client.get_latest_entries(category_id="your_category_id", count=20)

for entry in entries:
    if is_interesting(entry):  # Define your own criteria function
        # Keep it unread for later
        print(f"Keeping interesting entry: {entry.title}")
    else:
        # Mark as read
        client.mark_as_read(entry.id)
        print(f"Marked as read: {entry.title}")

Troubleshooting

Common Issues

• Authentication Errors: Ensure your Feedly access token is valid and has not expired
• Rate Limiting: Feedly API has rate limits. Consider adding delays between requests
• Connection Issues: Check your internet connection and Feedly API status

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.