Shared Team Memory for Claude Code: What Works Today
Claude Code memory is per-person. Your team's context is not. Here is how to give every engineer's Claude Code session one shared, versioned memory over MCP.
Claude Code memory is per-person. Your team's context is not. Here is how to give every engineer's Claude Code session one shared, versioned memory over MCP.
Handing a client the source code and prompt strings is not a handoff. They will edit the prompt, it will break, and you will get the 8 PM text. Ship the bundle instead: an eval suite, a shared source of truth, and a change trail.
Most AI memory tools only let the model read. Hjarni lets Claude and ChatGPT edit too: insert a line, fix a bullet, or delete a stale snippet without rewriting the whole note. Here's how surgical, conflict-safe editing works, and why writing back matters more than reading.
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A copy-paste CLAUDE.md for the Karpathy LLM wiki pattern: the schema, an annotated example wiki page, and the rules that make an agent maintain it. Works in Claude Code, with Obsidian or Logseq, or hosted over MCP in Hjarni.
Google Cloud's Open Knowledge Format (OKF) is folders of Markdown that AI agents can read. What the spec covers, why it matters, and how to export to it.
Mem0 and Supermemory are memory APIs for developers. Hjarni is a knowledge base your AI can read. How they store memory, what they cost, when to pick each.
Andrej Karpathy's LLM wiki gist nails it. Stop dumping documents at LLMs. Build a brain. Hjarni hosts it over MCP, in Claude and ChatGPT, on every device.
Connect Claude or ChatGPT to a hosted LLM wiki over MCP, no Obsidian and no terminal. A step-by-step setup you can finish in ten minutes.
Claude Code memory is per-person. Your team's context is not. Here is how to give every engineer's Claude Code session one shared, versioned memory over MCP.
Handing a client the source code and prompt strings is not a handoff. They will edit the prompt, it will break, and you will get the 8 PM text. Ship the bundle instead: an eval suite, a shared source of truth, and a change trail.
Most AI memory tools only let the model read. Hjarni lets Claude and ChatGPT edit too: insert a line, fix a bullet, or delete a stale snippet without rewriting the whole note. Here's how surgical, conflict-safe editing works, and why writing back matters more than reading.
A second brain is personal. In the AI era, teams need a shared one: notes each teammate can connect to their own Claude or ChatGPT. Here's what that looks like.
Your team already runs on an LLM wiki. It's just single-player. Here's how to build a shared knowledge base every teammate's Claude and ChatGPT can read.
A new hire's AI starts from zero, so they ask a senior engineer instead. Give the whole team's runbooks to a shared knowledge base and their assistant answers on day one.
Projects live inside one assistant, built for a focused task. A team needs shared context both Claude and ChatGPT can read. Here's the gap, and what closes it.
AI teams obsess over feeding the model the right context at the right time. You can do the same thing with your notes, so your AI pulls what it needs instead of you re-explaining yourself every session.
Indexing session transcripts sounds like memory. It mostly retrieves scratch work. The useful stuff was already distilled into artifacts. Keep the artifacts.
Most AI second brains fail because they dump too much into context. A useful AI memory uses retrieval, freshness, provenance, and short curated notes.
Anthropic donated MCP to a vendor-neutral foundation backed by its biggest rivals. Here is what that means, and why it makes a knowledge base built on MCP a safe bet instead of a single-vendor gamble.
Using MCP as your second brain means keeping your notes in one place and letting any AI client read and write them over the Model Context Protocol. Here's the pattern, the reference architecture, and how to run it.
AI agents forget everything between runs. The fix is a shared knowledge base they reach over MCP — read and write, human-readable, the same brain for every agent and every teammate. Here's the pattern.
Anthropic gave Claude a memory tool that stores memories as plain files on a disk. That is the right shape. Here is the job it does, and the job it still leaves to you: a knowledge base your AI can read.
You can connect Claude to a calendar, a CRM, a repo, and more. None of them remember anything. Here's how to think about the stack, and where durable memory fits beside it.
Some project tools now connect to Claude over MCP. But reading your tickets is not the same as remembering your decisions. Here's the difference, and where the memory layer goes.
Claude can connect to Gmail and search your inbox. But a thread you can find again is not a decision you can rely on. Here's where the durable facts go.
Claude can connect to your CRM and pull records and deal stages. But fields are not a relationship. Here's where the context behind the account goes.
Claude can connect to your calendar and see your schedule. But a calendar tells it when you meet, not what you decided. Here's where the context goes.
A copy-paste CLAUDE.md for the Karpathy LLM wiki pattern: the schema, an annotated example wiki page, and the rules that make an agent maintain it. Works in Claude Code, with Obsidian or Logseq, or hosted over MCP in Hjarni.
Google Cloud's Open Knowledge Format (OKF) is folders of Markdown that AI agents can read. What the spec covers, why it matters, and how to export to it.
Mem0 and Supermemory are memory APIs for developers. Hjarni is a knowledge base your AI can read. How they store memory, what they cost, when to pick each.
Six ways to give Claude or ChatGPT a memory in 2026, compared honestly. A knowledge base over MCP, built-in memory, projects, CLAUDE.md files, and more.
An honest roundup of the best MCP memory servers in 2026. Hjarni, Mem0, Supermemory, Zep, Letta, Basic Memory, and the official knowledge graph server compared.
OpenAI's 'Dreaming' upgrade makes ChatGPT remember more about you, automatically. Here is what it does well, and the job it still cannot do: be a knowledge base your AI can read.
Point Claude or ChatGPT at your own notes to run a literature review from the papers you actually read, with citations you can check, not invented.
Context engineering made code legible to coding agents. Your notes need the same thing. Capture is solved. Legibility is the bottleneck.
Eight rules for an LLM wiki your AI maintains over MCP: small notes, folders and tags that fit how you think, per-folder instructions, and summaries.
Running Karpathy's LLM wiki in an Obsidian vault versus a hosted knowledge base over MCP. What each one gives you, and an honest list of what you give up.
The daily Claude Code workflow for an LLM wiki, hosted over MCP instead of a local vault. Read context, write notes back, capture every session.
The "MCP is dead" posts are right about a real problem and wrong about the cause. Forty-two always-loaded tools is a design smell, not a protocol flaw. Here's where MCP actually wins.
A chat log is a transcript, not a knowledge base. Generation got good. Retrieval is the part that is still broken. Here is why, and what fixes it.
One click on any article saves a clean Markdown copy to your Hjarni inbox. The Chrome extension is live in the Web Store.
Connect Hjarni to Zapier to capture from Slack, Gmail, Calendar, and forms automatically. Then let ChatGPT search and use all of it. Five concrete workflows you can build today.
A second brain is a place outside your head where you store everything worth keeping. Here's what it is, why it matters, and why AI changes what it needs to do.
Connect a knowledge base to GitHub Copilot Chat via MCP so agent mode reads your architecture decisions and conventions. Full .vscode/mcp.json walkthrough included.
Five small workflows that turn Hjarni into memory for Claude and ChatGPT. Customer context, meeting notes, decision logs, a style guide your AI follows, and inbox leads handled while you sleep.
Most AI meeting tools transcribe. They don't help Claude remember what you decided. Here's how to give Claude and ChatGPT real meeting context via MCP.
A plain Markdown file works for the LLM wiki pattern. Until it doesn't. Here are the five points where it stops working, and what to use instead.
A second brain is an external system for what you read, think, and decide. The traditional version is a graveyard. Here's what replaces it in 2026.
A practical guide to using MCP with ChatGPT in 2026. Two ways to connect, real examples, and the troubleshooting steps nobody mentions.
Connect Cursor to your knowledge base over MCP, step by step. Your decisions and project context follow you across sessions, not just the code Cursor indexes.
Connect Claude or ChatGPT to a hosted LLM wiki over MCP, no Obsidian and no terminal. A step-by-step setup you can finish in ten minutes.
Hjarni is live in the ChatGPT Apps Directory. One click to connect. Your notes, your AI's memory.
I run Hjarni's entire growth program from inside Hjarni itself. Two AIs, three folders, and a built-in MCP server. Here's the real loop, step by step.
Notion has 47 features you'll never touch. Obsidian needs plugins for everything. Both assume you want a system. You don't. You want to write something down, find it later, and let your AI read it too.
OpenClaw is powerful but context-blind. Connect it to Hjarni and your agent stops starting from zero.
Andrej Karpathy's LLM wiki gist nails it. Stop dumping documents at LLMs. Build a brain. Hjarni hosts it over MCP, in Claude and ChatGPT, on every device.
Your AI is smart but has no memory. Here are five notes that fix that — so every conversation starts with context instead of from zero.
Learn how startups avoid information loss by using Hjarni's shared knowledge base.
Connect a knowledge base to Claude or ChatGPT via MCP so it remembers your projects and decisions across conversations. Full setup walkthrough included.
Every AI conversation eventually resets. The real cost isn't the limit — it's re-explaining yourself every time. Your knowledge deserves a home you own.
I connected Claude to my notes via MCP. Setup took 2 minutes. Now every conversation starts with my project context already loaded — no pasting, no re-explaining. Here is what changed about how I work.
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