What tools does MCP Server for Feedly API provide?
It provides `feedly.search`, `feedly.collect`, `feedly.entity_lookup`, and `feedly.autocomplete`.
@hafnium49
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp_server_feedly": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
}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.
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.
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.
pip install and environment variable.feedly.search tool.feedly.collect.feedly.entity_lookup.feedly.autocomplete.It provides `feedly.search`, `feedly.collect`, `feedly.entity_lookup`, and `feedly.autocomplete`.
Create a virtual environment, install `mcp`, `httpx`, and `python-dotenv`, export your `FEEDLY_TOKEN`, and run `python server.py`.
The server runs over HTTP on port 8080.
Yes, you must export your Feedly authentication token as the `FEEDLY_TOKEN` environment variable.
The discovery document is available at `http://localhost:8080/.well-known/mcp/`.

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