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br8n

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.

Related MCP server: memex-mcp

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.

Available Tools

3 tools
brain_listA
Read-onlyIdempotent

List every markdown file in the brain (relative path, size, last modified).

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds value by specifying the exact scope ('every markdown file') and the output fields, which clarifies what the tool returns without contradicting the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no wasted words. It front-loads the action and resource, then appends the relevant output fields in parentheses, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only list operation with annotations covering safety, the description is complete. It states what is listed, the scope, and the returned fields; no additional information is needed for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema is empty, so the baseline is 4. The description adds no parameter details, but none are needed; it instead describes the output characteristics, which is more useful for a parameterless tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List') and clearly identifies the resource ('every markdown file in the brain') plus the fields returned (relative path, size, last modified). This distinguishes it from siblings brain_read and brain_search, which imply reading or searching rather than enumerating.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'List every markdown file' provides clear context for when to use the tool: when the agent needs an inventory of all markdown files. It does not explicitly name alternatives or exclusions, so it stops short of a 5, but the intended usage is evident.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

brain_readA
Read-onlyIdempotent

Read one file from the brain by relative path (e.g. decisions/2026-03-change-orders.md).

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesrelative path inside the brain

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the scope of reading exactly one file and the relative-path constraint, but provides no details on error behavior or return format. These additions are consistent with annotations but minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence with action front-loaded, a precise resource, and a helpful example. No filler or redundancy; every part earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one required parameter, no output schema, and annotations covering side effects, the description is complete. The example and relative-path wording give the agent everything needed to call it correctly, and sibling tools provide surrounding context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already describes 'path' as a relative path, so the baseline is 3. The description goes slightly beyond by giving a concrete example (decisions/2026-03-change-orders.md), which clarifies the expected format and nested structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Read' with a clear resource ('one file from the brain') and a method ('by relative path') plus a concrete example. This distinguishes it naturally from siblings brain_list and brain_search without ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage—when you need the contents of a specific file by path—but does not explicitly contrast with brain_list or brain_search, nor does it state when not to use this tool. The context is clear enough but exclusions/alternatives are left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 3 tool updatesv0.1.2
    • First observedbrain_list
    • First observedbrain_read
    • First observedbrain_search

TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct operation: listing all files, reading a specific file, and searching content. There is no overlap or ambiguity in their purposes.

Naming Consistency5/5

All tools consistently use the 'brain_' prefix with a simple verb pattern (list/read/search), making the API predictable and easy to navigate.

Tool Count5/5

Three tools is minimal but well-scoped for a read-only markdown knowledge base. Each tool serves a necessary and non-redundant function.

Completeness4/5

The set fully covers the core retrieval workflows: browsing the structure, reading files, and searching content. Write or management operations are absent, but they appear outside the server's stated read-only scope.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

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