If you’ve ever wished your AI agent actually knew what you’d been working on for the past week — not just what you told it in the current session, but what you actually did on screen, in meetings, across every app — Screenpipe is the tool you’ve been waiting for.
Y Combinator’s S26 batch has produced a fascinating entry: Screenpipe, a local-first, source-available tool that continuously records your screen and audio on-device, indexes everything in SQLite, and exposes an MCP-compatible API on port 3030. That API lets AI agents query your real work context. Not summaries you remembered to write down. The actual record.
What Screenpipe Does
Screenpipe runs quietly in the background on your Mac, Windows, or Linux machine. Every window, every meeting, every document you open — it captures and indexes it locally. PII redaction is built in. Your data never leaves your machine unless you explicitly set it up to.
The result is a searchable memory layer that AI agents can query. From the Hacker News launch post, founder Louis Beaumont describes the core use case clearly: “an app that records your screen and audio locally (only!), and gives AI agents a searchable memory of what you’ve seen, said, and heard.”
Practically, that means your agent can answer questions like:
- “What did I discuss about pricing with the Acme client last month?”
- “Summarise my last five meetings.”
- “Write my weekly update from this week’s calls.”
- “Who asked about the Q3 budget this quarter?”
These aren’t hypotheticals — they’re shown in the product demo on screenpipe.com.
MCP-Native From Day One
This is where Screenpipe gets interesting for the agentic AI community specifically. The API exposed on port 3030 is MCP-compatible, which means agents that support MCP — including Claude (via Claude.ai), OpenClaw, Hermes, and others — can query your Screenpipe memory directly without custom integrations.
Screenpipe’s own concept of “pipes” (the name for its agent-triggered workflows) run on-device. Trigger conditions include events like meeting_ended, and a simple pipe.md file in Markdown defines what the agent should do when that trigger fires. The structure is intentionally simple:
---
name: meeting-notes
trigger: meeting_ended
model: local
---
When a meeting ends, write:
- 3-bullet summary
- Action items per person
- Decisions + next steps
Save to ~/notes/{date}_{app}.md
That runs entirely on-device with a local model, no API calls required.
A Founder’s Personal Obsession
Louis Beaumont (louis030195 on HN) has a genuine history here. He’s been maintaining a personal “second brain” since 2020 — journals, notes, music, conversations, CRM data. He built Ava, Obsidian’s first AI plugin, which grew to thousands of users. He built Embedbase, an API for making data AI-accessible. Screenpipe is the culmination of that multi-year obsession with giving AI agents real, personal context.
The HN launch got 79 points and 60 comments in its first hours — strong early traction for a developer tool, and unusual for a productivity app launch. The YC S26 backing signals the team has institutional support to build out the broader vision.
Why This Matters for Agent Practitioners
Context is the core problem in agentic AI. Agents are powerful, but they’re blind to everything that happened before the conversation started. RAG helps, but it requires someone to decide what to index. Screenpipe sidesteps that problem entirely — it indexes everything by default, and lets agents query it at runtime.
For anyone building or running agents for real knowledge work, this is a meaningful building block. Instead of manually writing summaries for your agent to read, you let Screenpipe capture what actually happened and let the agent query it when needed.
The local-first architecture also addresses the privacy concern that’s kept many organizations away from AI memory tools. If everything stays on your machine, there’s no data sharing risk. PII redaction adds an additional layer for sensitive environments.
The connections list on screenpipe.com includes Slack, Gmail, Notion, Linear, Google Calendar, GitHub, and dozens more — which means Screenpipe can push outputs from agent-triggered pipes into the tools you’re already using.
Available Now
Screenpipe is available for macOS, Windows, and Linux. It’s source-available on GitHub at screenpipe/screenpipe. You can try it free at screenpipe.com.
A how-to guide for connecting Screenpipe to OpenClaw — enabling your OpenClaw agents to query your real work history via MCP — is available on this site.
Sources
- Launch HN: Screenpipe (YC S26) — Record how you work and turn that into agents
- Screenpipe official site
- GitHub: screenpipe/screenpipe
- Y Combinator company directory: Screenpipe
Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260724-0800
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