Connections

Your data should live
where you already work

feed.works processes your podcasts & articles.
Connectors send the results, transcripts, summaries, etc to your storage.
No copy-pasting. No manual export. It just shows up.

You already have a system

Your notes live in Notion. Your files live in Dropbox. Maybe your AI reads data from S3. Connectors meet you where you are instead of asking you to check another app.

Automatic, not manual

Every new episode or article gets processed and synced without you doing anything. Subscribe once, connectors handle the rest. Your library grows in the background.

Your data, your infrastructure

Object-storage connectors (S3, R2, GCS) export to buckets you own. The MCP endpoint lets AI agents query your library directly. No intermediary. No vendor lock-in.

File Sync

Dropbox

Every transcript and summary lands as a file in your Dropbox.

Google Drive

Transcripts and summaries in your Drive, searchable by Google.

Knowledge Base

Notion

Each processed item becomes a page in a Notion database you control.

Obsidian

Markdown notes in your vault. Wiki-links between episodes that reference each other.

Object Storage

AWS S3

Raw export to your own bucket. Full control. Build your own pipelines.

Cloudflare R2

S3-compatible storage with zero egress fees. Predictable costs.

Google Cloud Storage

Export to GCS. Query with BigQuery. Pipe into Vertex AI.

Protocol

MCP Endpoint

Expose your library as a Model Context Protocol server. Any AI agent can query it.

Process your feeds. Send the results anywhere.

Start with the free plan. Add connectors when you're ready to send your library to the tools you already use.

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