OPML Podcast & RSS Parser MCP Server for AutoGenGive AutoGen instant access to 1 tools to Parse Opml Feeds
GDPR Free for SubscribersMicrosoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add OPML Podcast & RSS Parser as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
Ask AI about this MCP Server for AutoGen
The OPML Podcast & RSS Parser MCP Server for AutoGen is a standout in the Productivity category — giving your AI agent 1 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport 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="opml_podcast_rss_parser_agent",
tools=tools,
system_message=(
"You help users with OPML Podcast & RSS Parser. "
"1 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 OPML Podcast & RSS Parser MCP Server
When you want Claude to recommend new podcasts or blogs based on what you already consume, you export an .opml file from Apple Podcasts, Pocket Casts, or Feedly. But XML outlines are noisy, recursive, and confusing for LLMs to read efficiently.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use OPML Podcast & RSS Parser tools. Connect 1 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.
This MCP uses a fast, deterministic XML parser to flatten the OPML hierarchy into a simple, structured list of your subscriptions, dropping all the unnecessary XML tags and attributes.
The Superpowers
- Universal Support: Parses OPML files from any standard podcast player or RSS reader.
- Zero Token Waste: Converts heavy XML markup into a clean, flat JSON array.
- Local Privacy: Your subscription habits are parsed locally, ensuring they aren't uploaded to a public server.
- Assistant Ready: Turn Claude into your personal entertainment and news curator.
The OPML Podcast & RSS Parser MCP Server exposes 1 tools through the Vinkius. Connect it to AutoGen in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 1 OPML Podcast & RSS Parser tools available for AutoGen
When AutoGen connects to OPML Podcast & RSS Parser through Vinkius, your AI agent gets direct access to every tool listed below — spanning rss, podcast-management, xml-parsing, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Parse opml feeds on OPML Podcast & RSS Parser
Provide the absolute file path. Parse an OPML file (Podcast or RSS feed export) into a clean JSON list of subscriptions
Connect OPML Podcast & RSS Parser to AutoGen via MCP
Follow these steps to wire OPML Podcast & RSS Parser into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind 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 OPML Podcast & RSS Parser MCP Server
AutoGen provides unique advantages when paired with OPML Podcast & RSS Parser through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use OPML Podcast & RSS Parser tools to solve complex tasks
Role-based architecture lets you assign OPML Podcast & RSS Parser 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 OPML Podcast & RSS Parser tool calls
Code execution sandbox: AutoGen agents can write and run code that processes OPML Podcast & RSS Parser tool responses in an isolated environment
OPML Podcast & RSS Parser + AutoGen Use Cases
Practical scenarios where AutoGen combined with the OPML Podcast & RSS Parser MCP Server delivers measurable value.
Collaborative analysis: one agent queries OPML Podcast & RSS Parser while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from OPML Podcast & RSS Parser, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using OPML Podcast & RSS Parser data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process OPML Podcast & RSS Parser responses in a sandboxed execution environment
Example Prompts for OPML Podcast & RSS Parser in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with OPML Podcast & RSS Parser immediately.
"Read my podcasts.opml file and recommend 3 new tech podcasts I might like."
"Extract all the RSS URLs from my Feedly export and format them as a Markdown table."
"Analyze my OPML file and tell me what my primary interests are."
Troubleshooting OPML Podcast & RSS Parser MCP Server with AutoGen
Common issues when connecting OPML Podcast & RSS Parser to AutoGen through Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"OPML Podcast & RSS Parser + AutoGen FAQ
Common questions about integrating OPML Podcast & RSS Parser MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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