memokar/brainy

Shared brain for your AI agents: self-hosted knowledge + task backbone for Claude, ChatGPT & any MCP client. Git-versioned Markdown, atomic task claims, ACL, audit. Zero dependencies.

Python

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9 commits

updated Oct 6, 2026

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I got tired of Claude and ChatGPT not knowing what the other one did, so I built them a shared brain (open source) (r/mcp)

Some context: I'm a solo guy running a handful of small online brands in Germany (merch shops, social pages, a bunch of little tools). I use Claude, ChatGPT and Codex every day, and the annoying part was always the same: each one starts from zero. I'd explain a decision to Claude, then ChatGPT knew…

2

Oct 6, 2026

README

Brainy

CI License: AGPL-3.0 Dependencies: none

A shared brain for your AI agents — and for the humans who work with them.

Brainy is a self-hosted knowledge and task backbone that Claude, ChatGPT and any other MCP-capable AI connect to through one controlled endpoint. Every agent reads the same knowledge, works on the same task list and leaves an audit trail — so your AIs can hand work to each other instead of living in separate chat silos.

   ChatGPT ─┐                                   ┌─ Git-versioned knowledge (Markdown)
   Claude  ─┼──►  MCP endpoint  ──►  Brainy  ───┼─ Tasks with atomic claim/lease
   Your bot ┘     (OAuth / tokens)   ACL+Audit  └─ Spaces, roles, append-only audit log
                                       ▲
                          Humans: web admin UI (+ optional Telegram approvals)

Why Brainy?

  • AIs that collaborate. ChatGPT creates a task, Claude claims it, does the work and writes the result back; a human reviews. Coordination happens through tasks — no hidden agent-to-agent magic.
  • One source of truth. Knowledge lives as plain Markdown in a Git repository. Every write is a commit, so you get history, diffs and rollback for free.
  • Safe by default. No shell, no filesystem, no eval over MCP. Path allowlist, per-space ACLs, secret detection on writes, rate limits, hashed tokens and an append-only audit log.
  • No double work. Atomic task claims with leases and claim tokens guarantee that two agents never process the same task at the same time.
  • Human in the loop. Agents can propose knowledge changes; a human approves or rejects them (web UI or Telegram). Tasks can require review/approval before they count as done.
  • Zero dependencies. Pure Python standard library + SQLite. No pip install, tiny attack surface.

Features

AreaWhat you get
Knowledgelist_documents, get_document, search_knowledge, write_document (optimistic concurrency via Git commit), append_document, propose_write
Taskscreate_task, claim_task, renew_claim, complete_task, fail_task, release_task, dependencies, priorities, review/approve/reject
AccessSpaces (tenants/areas), roles ADMIN / EDITOR / AGENT / READER, per-space ACL, service tokens, OAuth 2.1 (for Claude/ChatGPT remote connectors)
OperationsWeb admin UI, audit log, agent registry + dispatcher framework, backup & verified restore scripts

Quickstart (Docker)

Prebuilt image (published on every release):

docker run -d --name brainy -p 127.0.0.1:8765:8765 -v brainy-data:/data ghcr.io/memokar/brainy:latest
docker logs brainy   # prints your one-time ADMIN token on first start

Or build it yourself with Compose:

git clone https://github.com/memokar/brainy.git
cd brainy
docker compose up -d
docker compose logs brainy   # prints your one-time ADMIN token on first start

Brainy now listens on http://127.0.0.1:8765 (MCP endpoint: /mcp, admin UI: /admin — log in with the token). For remote AI connectors put it behind HTTPS (see deploy/nginx-brainy.conf.example) and set BRAINY_PUBLIC_BASE_URL.

Quickstart (bare metal, Linux, Python ≥ 3.10)

export BRAINY_DB_PATH=$PWD/data/brainy.db
export BRAINY_KNOWLEDGE_ROOT=$PWD/data/knowledge
export BRAINY_WEB_SESSION_KEY=$PWD/data/web_session.key

cp -r examples/knowledge "$BRAINY_KNOWLEDGE_ROOT"
git -C "$BRAINY_KNOWLEDGE_ROOT" init -q && git -C "$BRAINY_KNOWLEDGE_ROOT" add -A \
  && git -C "$BRAINY_KNOWLEDGE_ROOT" commit -qm "initial knowledge"

python3 scripts/bootstrap.py "$BRAINY_DB_PATH" --with-token   # prints ADMIN token once
python3 scripts/init_prod_db.py "$BRAINY_DB_PATH"             # seeds default spaces
python3 scripts/serve.py

Connecting an AI

  • Claude Code:
    claude mcp add --transport http brainy http://127.0.0.1:8765/mcp --header "Authorization: Bearer <token>"
    
  • Local stdio clients (e.g. Claude Desktop): run Brainy as a subprocess:
    {"mcpServers": {"brainy": {"command": "python3", "args": ["/opt/brainy/scripts/stdio.py"],
      "env": {"BRAINY_DB_PATH": "/var/lib/brainy/brainy.db",
              "BRAINY_KNOWLEDGE_ROOT": "/opt/brainy-knowledge", "BRAINY_TOKEN": "<token>"}}}}
    
    Try it without any setup: python3 scripts/stdio.py --demo (temporary data, deleted on exit).
  • Any other MCP client with custom headers: endpoint https://<your-host>/mcp, header Authorization: Bearer <service token>.
  • Claude.ai / ChatGPT remote connectors: use the OAuth 2.1 flow (discovery at /.well-known/oauth-authorization-server). Set BRAINY_PUBLIC_BASE_URL to your HTTPS URL.

Brainy is listed in the official MCP Registry as io.github.memokar/brainy.

Give each AI its own principal (e.g. claude, chatgpt) with role AGENT and only the spaces it needs. Every action then shows up in the audit log under that name.

Configuration

All configuration comes from environment variables — see .env.example. Secrets (tokens, keys) are never stored in the repository or the knowledge base.

Extensions

The core ships a worker plugin interface and a deterministic MockWorker. Real workers that let agents execute tasks autonomously (e.g. Claude Code, Codex) are separate extensions loaded via BRAINY_WORKER_PLUGINS. See docs/extensions.md.

Running the tests

for t in tests/test_*.py; do python3 "$t" || exit 1; done

Status & roadmap

Brainy runs in production for its author. Current limitations:

  • Code comments are still partly German; all user-facing text is English.
  • Single-node design (SQLite). PostgreSQL only if real multi-writer load appears.

License

Copyright (C) 2026 Mehmet Karakolcu

Brainy is dual-licensed:

  • Open source: GNU AGPL-3.0. Free for everyone, including companies — but if you modify Brainy and offer it to others (also as a network service), you must publish your changes under the AGPL.
  • Commercial license: for companies that want to use or embed Brainy without AGPL obligations. See COMMERCIAL.md.

Contributions require agreeing to the Contributor License Agreement.

ai-agents
chatgpt
claude
knowledge-base
mcp
model-context-protocol
python
self-hosted
sqlite
task-queue

memokar/brainy

Shared brain for your AI agents: self-hosted knowledge + task backbone for Claude, ChatGPT & any MCP client. Git-versioned Markdown, atomic task claims, ACL, audit. Zero dependencies.

Python

0

9 commits

updated Oct 6, 2026

See the code

See what people are saying

SourceMessageScoreDate

I got tired of Claude and ChatGPT not knowing what the other one did, so I built them a shared brain (open source) (r/mcp)

Some context: I'm a solo guy running a handful of small online brands in Germany (merch shops, social pages, a bunch of little tools). I use Claude, ChatGPT and Codex every day, and the annoying part was always the same: each one starts from zero. I'd explain a decision to Claude, then ChatGPT knew…

2

Oct 6, 2026

README

Brainy

CI License: AGPL-3.0 Dependencies: none

A shared brain for your AI agents — and for the humans who work with them.

Brainy is a self-hosted knowledge and task backbone that Claude, ChatGPT and any other MCP-capable AI connect to through one controlled endpoint. Every agent reads the same knowledge, works on the same task list and leaves an audit trail — so your AIs can hand work to each other instead of living in separate chat silos.

   ChatGPT ─┐                                   ┌─ Git-versioned knowledge (Markdown)
   Claude  ─┼──►  MCP endpoint  ──►  Brainy  ───┼─ Tasks with atomic claim/lease
   Your bot ┘     (OAuth / tokens)   ACL+Audit  └─ Spaces, roles, append-only audit log
                                       ▲
                          Humans: web admin UI (+ optional Telegram approvals)

Why Brainy?

  • AIs that collaborate. ChatGPT creates a task, Claude claims it, does the work and writes the result back; a human reviews. Coordination happens through tasks — no hidden agent-to-agent magic.
  • One source of truth. Knowledge lives as plain Markdown in a Git repository. Every write is a commit, so you get history, diffs and rollback for free.
  • Safe by default. No shell, no filesystem, no eval over MCP. Path allowlist, per-space ACLs, secret detection on writes, rate limits, hashed tokens and an append-only audit log.
  • No double work. Atomic task claims with leases and claim tokens guarantee that two agents never process the same task at the same time.
  • Human in the loop. Agents can propose knowledge changes; a human approves or rejects them (web UI or Telegram). Tasks can require review/approval before they count as done.
  • Zero dependencies. Pure Python standard library + SQLite. No pip install, tiny attack surface.

Features

AreaWhat you get
Knowledgelist_documents, get_document, search_knowledge, write_document (optimistic concurrency via Git commit), append_document, propose_write
Taskscreate_task, claim_task, renew_claim, complete_task, fail_task, release_task, dependencies, priorities, review/approve/reject
AccessSpaces (tenants/areas), roles ADMIN / EDITOR / AGENT / READER, per-space ACL, service tokens, OAuth 2.1 (for Claude/ChatGPT remote connectors)
OperationsWeb admin UI, audit log, agent registry + dispatcher framework, backup & verified restore scripts

Quickstart (Docker)

Prebuilt image (published on every release):

docker run -d --name brainy -p 127.0.0.1:8765:8765 -v brainy-data:/data ghcr.io/memokar/brainy:latest
docker logs brainy   # prints your one-time ADMIN token on first start

Or build it yourself with Compose:

git clone https://github.com/memokar/brainy.git
cd brainy
docker compose up -d
docker compose logs brainy   # prints your one-time ADMIN token on first start

Brainy now listens on http://127.0.0.1:8765 (MCP endpoint: /mcp, admin UI: /admin — log in with the token). For remote AI connectors put it behind HTTPS (see deploy/nginx-brainy.conf.example) and set BRAINY_PUBLIC_BASE_URL.

Quickstart (bare metal, Linux, Python ≥ 3.10)

export BRAINY_DB_PATH=$PWD/data/brainy.db
export BRAINY_KNOWLEDGE_ROOT=$PWD/data/knowledge
export BRAINY_WEB_SESSION_KEY=$PWD/data/web_session.key

cp -r examples/knowledge "$BRAINY_KNOWLEDGE_ROOT"
git -C "$BRAINY_KNOWLEDGE_ROOT" init -q && git -C "$BRAINY_KNOWLEDGE_ROOT" add -A \
  && git -C "$BRAINY_KNOWLEDGE_ROOT" commit -qm "initial knowledge"

python3 scripts/bootstrap.py "$BRAINY_DB_PATH" --with-token   # prints ADMIN token once
python3 scripts/init_prod_db.py "$BRAINY_DB_PATH"             # seeds default spaces
python3 scripts/serve.py

Connecting an AI

  • Claude Code:
    claude mcp add --transport http brainy http://127.0.0.1:8765/mcp --header "Authorization: Bearer <token>"
    
  • Local stdio clients (e.g. Claude Desktop): run Brainy as a subprocess:
    {"mcpServers": {"brainy": {"command": "python3", "args": ["/opt/brainy/scripts/stdio.py"],
      "env": {"BRAINY_DB_PATH": "/var/lib/brainy/brainy.db",
              "BRAINY_KNOWLEDGE_ROOT": "/opt/brainy-knowledge", "BRAINY_TOKEN": "<token>"}}}}
    
    Try it without any setup: python3 scripts/stdio.py --demo (temporary data, deleted on exit).
  • Any other MCP client with custom headers: endpoint https://<your-host>/mcp, header Authorization: Bearer <service token>.
  • Claude.ai / ChatGPT remote connectors: use the OAuth 2.1 flow (discovery at /.well-known/oauth-authorization-server). Set BRAINY_PUBLIC_BASE_URL to your HTTPS URL.

Brainy is listed in the official MCP Registry as io.github.memokar/brainy.

Give each AI its own principal (e.g. claude, chatgpt) with role AGENT and only the spaces it needs. Every action then shows up in the audit log under that name.

Configuration

All configuration comes from environment variables — see .env.example. Secrets (tokens, keys) are never stored in the repository or the knowledge base.

Extensions

The core ships a worker plugin interface and a deterministic MockWorker. Real workers that let agents execute tasks autonomously (e.g. Claude Code, Codex) are separate extensions loaded via BRAINY_WORKER_PLUGINS. See docs/extensions.md.

Running the tests

for t in tests/test_*.py; do python3 "$t" || exit 1; done

Status & roadmap

Brainy runs in production for its author. Current limitations:

  • Code comments are still partly German; all user-facing text is English.
  • Single-node design (SQLite). PostgreSQL only if real multi-writer load appears.

License

Copyright (C) 2026 Mehmet Karakolcu

Brainy is dual-licensed:

  • Open source: GNU AGPL-3.0. Free for everyone, including companies — but if you modify Brainy and offer it to others (also as a network service), you must publish your changes under the AGPL.
  • Commercial license: for companies that want to use or embed Brainy without AGPL obligations. See COMMERCIAL.md.

Contributions require agreeing to the Contributor License Agreement.

ai-agents
chatgpt
claude
knowledge-base
mcp
model-context-protocol
python
self-hosted
sqlite
task-queue