About br8n
br8n is a Markdown file template and small MCP server for teams that want portable working memory readable by any model. Its three tools search and read files, returning file and line references for sourced answers.
Key features
- 01Markdown-based brain layout
- 02List and read brain files
- 03Search with file and line references
- 04Portable, inspectable file storage
Use cases
- 01Give a model access to team decisions
- 02Find documented work practices and exceptions
- 03Check new work against recorded decisions
MCP support
The stdio MCP server exposes `brain_list`, `brain_read` and `brain_search` to MCP clients, allowing models to read and search a local brain directory.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
3Saved tool list · updated 2w ago
This tool takes no parameters.
Details
From the project READMEbr8n
Owned, portable working memory. A plain-files brain template and a tiny MCP server that lets any model read it.
Everything your team has taught a chat tool about how the work gets done is sitting inside somebody else's login. Switch tools and you're a stranger again. This repo is the other direction: the memory lives in files you own, and the model is just a reader.
br8n is the AI delivery practice of Branded Mayhem Collective. This is the open part: the file layout and the door. The hosted install adds retrieval, governance, and someone running it with you — on the same files, which never change shape. br8n.io
What's here
template/brain/— the brain layout:how-we-work/,decisions/,exceptions/,handoffs/,voice/. Markdown only. One file, one thing. Write the why, so the model can push back later.src/— an MCP server (stdio) with three tools:brain_list,brain_read,brain_search. Search returns file + line so answers cite their source. No vectors, no index, no account. Grep is the point.
Use it
npx @br8n/mcp ~/my-brain # MCP server on stdio (or: npm i -g @br8n/mcp && br8n ~/my-brain)
# template: git clone https://github.com/Branded-Mayhem-Collective-LLC/br8n && cp -r br8n/template/brain ~/my-brain
Claude Desktop / Claude Code / Cursor (any MCP client) — add:
{ "mcpServers": { "br8n": { "command": "npx", "args": ["-y", "@br8n/mcp", "/path/to/my-brain"] } } }
Then ask the model something the brain knows. It answers from the file and names it. Switch the model; same answer, same file.
Why files
- Portable.
cp -r brain/ new-machine/is the whole migration. If you can't do that, you don't own it. - Inspectable. You can read every byte the model reads.
- Model-agnostic. The folder doesn't care which model is on the other side of MCP.
- It can push back. A decision stored with its why lets a model say "this conflicts with what you decided in March." A chat history can't.
The method is public on purpose
The layout and this server are MIT. What br8n charges for is hands on a real operation: eliciting what's actually in people's heads, shaping retrieval for the role, running it, and keeping it current. If you'd rather do it yourself, start here — most people should. The free first course is at br8n.io/lab.
Not affiliated
br8n on PyPI (a context-capture engine by a different author) is not this project.
MIT © 2026 Branded Mayhem Collective LLC
Publishing (maintainers)
Configure npm's trusted publisher once for @br8n/mcp:
- Publisher: GitHub Actions
- Organization:
Branded-Mayhem-Collective-LLC - Repository:
br8n - Workflow:
publish.yml - Allowed action:
npm publish
Publish the version already committed to main, then update the official MCP Registry:
gh workflow run publish.yml --ref main -f version=0.1.2
gh run watch --exit-status
mcp-publisher login github
mcp-publisher publish
The GitHub-hosted workflow uses npm trusted publishing (OIDC), so it requires no long-lived npm token. Change the version argument for future releases.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.