Feedly MCP Server for AutoGenGive AutoGen instant access to 10 tools to Get Article Details, Get Feed Metadata, Get Stream Contents, and more
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Feedly as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
Ask AI about this App Connector for AutoGen
The Feedly app connector for AutoGen is a standout in the Productivity category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="feedly_alternative_agent",
tools=tools,
system_message=(
"You help users with Feedly. "
"10 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Feedly MCP Server
Connect your Feedly account to any AI agent and take full control of your news aggregation and content curation workflows through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Feedly tools. Connect 10 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Feed Orchestration — List and manage your subscribed news sources programmatically, including adding or removing RSS/Atom feeds
- Stream Intelligence — Retrieve the latest entries (articles) from specific feeds or categories and monitor unread counts in real-time
- Content Extraction — Programmatically fetch complete article text and metadata to perform deep analysis and summaries via your agent
- Organization Control — Manage your Feedly categories and personal tags to maintain a structured and high-fidelity reading environment
- Reading Workflow — Mark articles as read and manage your reading list programmatically to streamline your news consumption
The Feedly MCP Server exposes 10 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 10 Feedly tools available for AutoGen
When AutoGen connects to Feedly through Vinkius, your AI agent gets direct access to every tool listed below — spanning rss-aggregator, content-curation, industry-trends, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Get full content of an article
Get metadata for a specific feed
Retrieve articles from a stream
Get your Feedly profile
List your Feedly categories
List all subscribed feeds
List your personal tags
Mark one or more articles as read
Follow a new news source
Stop following a news source
Connect Feedly to AutoGen via MCP
Follow these steps to wire Feedly into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install AutoGen
pip install "autogen-ext[mcp]"Replace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenIntegrate into workflow
Explore tools
Why Use AutoGen with the Feedly MCP Server
AutoGen provides unique advantages when paired with Feedly through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Feedly tools to solve complex tasks
Role-based architecture lets you assign Feedly tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Feedly tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Feedly tool responses in an isolated environment
Feedly + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Feedly MCP Server delivers measurable value.
Collaborative analysis: one agent queries Feedly while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Feedly, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Feedly data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Feedly responses in a sandboxed execution environment
Example Prompts for Feedly in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Feedly immediately.
"List all my categories in Feedly."
"Show me the last 3 unread articles in the 'AI & ML' category."
"Subscribe to this feed: 'https://example.com/rss' and add it to 'Tech'."
Troubleshooting Feedly MCP Server with AutoGen
Common issues when connecting Feedly to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Feedly + AutoGen FAQ
Common questions about integrating Feedly MCP Server with AutoGen.