SurfSense

SurfSense began as an open-source alternative to NotebookLM and now aims at a second problem: giving agents somewhere trustworthy to look when the answer lives on Reddit, in a video transcript or under a product review. Official platform APIs are rate-limited or priced for enterprises, scraping plumbing is brittle, and driving a browser with a model burns minutes per page.

Every source is a REST endpoint returning structured JSON, and the same set is published as an MCP server so Claude, Cursor or any agent framework can call them as native tools. Retries, structured output and credit metering come with the harness.

Behind the connectors, the research workspace that made the project popular is still in place.

• Connector catalog: Reddit, YouTube, Instagram, TikTok, Amazon, Walmart, Google Maps, Google Search, Indeed and open web crawling.
• Knowledge base: upload documents or sync Google Drive, OneDrive and Dropbox, then search with cited answers.
• Deliverables: reports, spreadsheets, slide decks, narrated video overviews and two-host podcasts built from your material.
• Automations: agent runs on a schedule or on events, writing results back to Notion, Slack, Linear and Jira.
• Team access: real-time collaborative chats with comments, plus owner, admin, editor and viewer roles.

Self-hosting needs Docker Desktop and ships with billing switched off, so crawls and agent runs are bounded only by your hardware and the model keys you bring. Over a hundred models are reachable through the OpenAI spec and LiteLLM, local inference included.