MCP Server for Feedly API

@hafnium49

Repository

Basic information

About MCP Server for Feedly API

No overview available yet

#mcp-server#feedly-api#python-sdk

MCP Server for Feedly API config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp_server_feedly": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

MCP Server for Feedly API tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP Server for Feedly API?

A minimal Python SDK server that exposes selected Feedly API endpoints (search, collect, entity lookup, autocomplete) as MCP tools. It allows MCP-aware language models to search and retrieve articles or NLP entity information from Feedly.

How to use MCP Server for Feedly API?

Create a Python virtual environment, install dependencies (mcp, httpx, python-dotenv), export your FEEDLY_TOKEN, and run python server.py. The server listens on HTTP port 8080 and provides four tools: feedly.search, feedly.collect, feedly.entity_lookup, and feedly.autocomplete.

Key features of MCP Server for Feedly API

Exposes four Feedly API endpoints as MCP tools.
Requires a Feedly authentication token.
Runs over HTTP on port 8080.
Built with the Python MCP SDK and httpx.
Minimal setup with pip install and environment variable.

Use cases of MCP Server for Feedly API

Search Feedly for articles using the feedly.search tool.
Collect full article content with feedly.collect.
Perform NLP entity lookups via feedly.entity_lookup.
Get autocomplete suggestions with feedly.autocomplete.

Frequently asked questions

What tools does MCP Server for Feedly API provide?

It provides `feedly.search`, `feedly.collect`, `feedly.entity_lookup`, and `feedly.autocomplete`.

How do I install and run the server?

Create a virtual environment, install `mcp`, `httpx`, and `python-dotenv`, export your `FEEDLY_TOKEN`, and run `python server.py`.

What transport does the server use?

The server runs over HTTP on port 8080.

Do I need an API key to use the server?

Yes, you must export your Feedly authentication token as the `FEEDLY_TOKEN` environment variable.

Where can I find the MCP discovery document?

The discovery document is available at `http://localhost:8080/.well-known/mcp/`.

Comments

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