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OneLamp is the shared context layer for all your AI tools. You use the best AI tool for each task (Claude Code, Codex, Cursor, ChatGPT, whatever ships next) — but they don’t share what they learn, so moving context between them falls to you. OneLamp carries what each tool learns to the next over a single MCP endpoint, so every tool works from what the others already know.

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The problem

You use the best AI tool for each task, but they don’t share what they learn. What Claude learns, Gemini never sees; ChatGPT’s memory never reaches your editor’s tool. So moving context between them is manual — that’s you, re-explaining yourself at every handoff. And the barrier is structural: an AI provider’s memory is single-provider by definition, and no one is incentivized to bridge the silos, so they stay permanent. Only a neutral layer can be cross-provider.

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How OneLamp solves it

OneLamp sits across all your AI tools as one context layer. Every tool contributes what it learns; every tool uses what the others already know. Teach one, and they all learn, so you never have to repeat yourself.

Connect once, use everywhere

Link your tool to one personal MCP endpoint. Every tool that speaks MCP reads and writes your context through the same tiny surface.

Retrieval, not generation

The default query path returns a ranked pack of your material to reason over — never a synthesized answer that drifts from the source.

Cross-provider by design

Move from Claude to Gemini to Codex and the next tool already knows you. Your context follows you, not the other way around.

You own your data

Your context lives in your own per-user store. Export the whole thing as portable JSON at any time.

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How it works

1

Sign in

Create a OneLamp account at app.onelamp.ai with GitHub, Google, or email.
2

Connect a client

Copy your personal MCP endpoint and add it to any AI client. The client signs in to OneLamp once via OAuth; no API keys to manage.
3

Seed it once (optional)

Run /ol, or point any tool at app.onelamp.ai/setup.md, to pull in what a tool already knows about you. See the Quickstart.
4

Work as usual

Each tool loads relevant context at the start of a task and saves durable learnings as it goes — automatically in clients that support hooks. The next tool uses all of it.

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What’s live today

OneLamp is in closed alpha (Phase 0). The shipping product is the personal MCP endpoint and its tools:
  • Context memory — save_context, save_session, get_context, list_context, resume_session, and forget_context give any tool durable, portable context. These six memory-CRUD tools are the entire MCP surface. See Context memory.
  • Library — ingest documents and URLs into an interlinked, tool-maintained Library you can query, managed from the OneLamp web app. See Library.
  • Data sources — connect your other tools (Notion, Drive, Slack) over MCP and index their content on demand into your context, from the web app’s Data Sources page. See Data sources.
New to OneLamp? The Quickstart gets you from sign-up to a connected tool in a few minutes.

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Principles

Tool-agnostic

Models come and go. Your context shouldn’t.

Zero friction

If it takes effort to maintain, it’s already failed.

Privacy-first

Your context is yours. Period.