<p align="center" <a href="https://joinstash.ai"<img src="docs/assets/logo.svg" alt="Stash" width="320" /</a </p
<h3 align="center"Knowledge bases for the agent era.</h3
<p align="center" The one place your agents connect to all your data — GitHub, Drive, Gmail, Notion, <br Slack, Linear, Jira, Asana, Granola and more — plus an agent-native Drive in <br Markdown and HTML where their sessions, files, and pages all land. </p
<p align="center" <a href="https://github.com/Fergana-Labs/stash/actions/workflows/test.yml"<img src="https://github.com/Fergana-Labs/stash/actions/workflows/test.yml/badge.svg?branch=main" alt="CI" /</a <a href="LICENSE"<img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License: MIT" /</a <a href="https://joinstash.ai"<img src="https://img.shields.io/badge/Website-joinstash.ai-F97316" alt="Website" /</a <a href="#self-hosted"<img src="https://img.shields.io/badge/Self--hostable-✓-22C55E" alt="Self-hostable" /</a <a href="#privacy"<img src="https://img.shields.io/badge/Transcripts-opt--in-3B82F6" alt="Opt-in transcripts" /</a <a href="https://discord.gg/PVFdcQx2u3"<img src="https://img.shields.io/badge/Discord-Join%20us-5865F2?logo=discord&logoColor=white" alt="Discord" /</a </p <p align="center" When we tested this internally, we found that it sped up long-running instances of Claude Code by <a href="https://henrydowling.com/agent-velocity.html"<b49%</b</a.<br/ </p
<p align="center" <img src="docs/assets/memory.png" alt="Stash Memory — wiki knowledge graph, file system, and recent agent activity" width="900" / </p <!-- GIF #2 — The product in action: agent runs stash search, gets a cited answer --
<p align="center" <img src="docs/assets/product.gif" alt="Stash in action — agent queries shared memory and gets cited answers" width="900" / </p
How it works
- Sessions stream in automatically. A hook for your coding agent pushes every transcript — prompts, tool calls, artifacts — into your Stash.
- Files and sessions live side by side. Markdown, HTML, tables, PDFs. You and your agents both write here; both sides see edits in real time.
- Agents query it like a filesystem. A CLI, MCP server (~70 read/write tools), REST API, and virtual-filesystem shell expose your Stash to any agent. One search spans your pages, sessions, and every connected source at once.
- There's an agent in the box too. Chat with an agent that already has all of this — in the app, from Slack, or from Telegram. It's a real coding-agent CLI (Claude Code, Codex, or opencode) running on your own cloud VM, so it can read, write, and run things. Give it a cron and it becomes a scheduled agent.
- Memory is a wiki an agent keeps for you. A scheduled curator reads whatever is new since its last run — sessions, files, saves — and compiles it into linked pages: entities, concepts, and a running log. It writes only inside the reserved Memory folder, and never reads its own output.
- Skills are the shareable slice. A Skill is just a folder with a SKILL.md in it — put the pages, files, and tables that belong together in one folder and it becomes shareable as a unit. Publish it to the world, fork a public Skill into your own Stash, or stash skills install one into your agent — installed skills auto-update at session start, and stash skills follow auto-installs skills people share with you.
- Bring your own MCP servers. Register MCP servers once (Tools page or stash tools add); your cloud agent gets them automatically and stash tools install writes them into any local agent's .mcp.json.
Why persistent beats per-session
When you run Claude on a repo, you generate valuable session transcripts. However, your coding agent can only access transcripts generated on the machine where the agent is currently running. As a result, work is duplicated and velocity is decreased. This is especially true as coding agents begin to run autonomously for significant periods of time.
With Stash, every agent run has context about every session you've created. Here are some use cases:
- Code Faster / Don't Duplicate Work: "Have I tried fixing the memory leak in our API gateway before? What was attempted?"
- Stay Organized: "What did I get done this week? What other work did I do that isn't tracked in Git?"
- Recover Lost Context: "Why did I increase the timeout to 30s? The git history is unhelpful."
- Pick Up Where You Left Off: "Please add a feedback endpoint to our API" - Claude: "FYI, you decided earlier not to add a feedback endpoint since we want to encourage churned users to hop on a call directly"
"raw data from a given number of sources is collected, then compiled by an LLM into a .md knowledge base, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance it… I think there is room here for an incredible new product instead of a hacky collection of scripts." — Andrej Karpathy, LLM Knowledge Bases
Stash is that product. The one place your agents connect to all your data, with an agent-native Drive they write it back into — not a stack of shell scripts wrapped around a folder of markdown.
Built for —
| Use case | What teams put in it | |---|---| | Engineering live docs | coding-agent plans, ADRs, and design notes that stay current | | Second brain | the persistent context every one of your agents reads from | | Research knowledge base | long-running PKBs with sources, transcripts, and tables | | Ops playbooks | release runbooks and on-call procedures | | Brand voice | editorial guidelines and copy standards agents write to | | Personal knowledge management | notes, drafts, and scratch files for a single operator |