BrandMan MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@BrandMan MCP ServerDraft a launch post in our brand voice for the demo-brand"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
BrandMan
BrandMan is an agent-first brand brain. It keeps a brand's mission, voice, compliance rules, audience personas, content sources, campaigns and results in one governed place, and lets AI agents (through MCP) and people (through a dashboard) work from that same source of truth.
Channels are replaceable adapters. X, a newsletter platform or your own site sit at the edge: BrandMan drafts for them, records what happened, and learns from the results. The brand context itself never lives inside a channel.
Status: early. The core runs and is tested, but expect rough edges and breaking changes. Nothing is published to a channel automatically; posting is handed off for explicit approval.
What is in the core
Brand context: mission, voice, guidelines, personas and policy per brand, retrievable by agents and humans.
Content workflow: sources, campaigns, channel drafts, exact-revision approval, and a governed delivery handoff.
Feedback loop: record channel outcomes, propose evidence-backed learnings, and accept them into the brand context only on explicit approval.
KPI missions: time-boxed goals with baselines, targets and trajectory, fed by connector observations.
MCP server: the same flows exposed to any MCP-compatible agent, over stdio or a hosted OAuth-protected HTTP endpoint.
Dashboard and REST API: an operator UI and the API behind it.
Related MCP server: Brand Registry
Two ways to run it
Self-hosted (this repository): run the whole thing yourself against a local SQLite database. This repository is licensed AGPL-3.0.
Managed: a hosted offering built on this core plus separate closed components (billing, multi-tenancy and similar). Not part of this repository.
Quickstart
Requirements for a source checkout: Python 3.11+, uv, and Node.js 22.12+ with npm.
Legacy aliases. The product is BrandMan. For compatibility with existing installs, the
brand-os-*commands,BRAND_OS_*environment variables and thebrandos_sessioncookie name still work; thebrandman-*commands are the primary names.
git clone https://github.com/AustinNChristensen/brandman.git
cd brandman
uv sync --locked
uv run python scripts/build_dashboard.py
uv run brandman init # asks for your brand; writes .env and the database
uv run brandman serve # http://127.0.0.1:8000/app (password is in .env)
uv run brandman mcp-config --client claude-code # connect an agentOr with Docker: cp .env.example .env, set BRANDMAN_PREVIEW_PASSWORD, then
docker compose up -d.
The source HTML (web/index.html) and React code are tracked; generated files in
brandman/static/app/ are ignored. After changing dashboard source, rerun
uv run python scripts/build_dashboard.py before serving it or running Python
HTTP tests. npm run dev in web/ remains available for frontend development.
For a release or deployment, run uv build with Node.js available. The wheel
build hook installs the locked frontend dependencies and builds the dashboard,
then includes all generated assets in the wheel. Install that wheel in the
runtime environment; Node.js is only needed by the build machine. Source archives
include the frontend sources and build hook, and rebuild the assets when converted
to a wheel. Editable installs do not run frontend builds automatically.
Builders without Node/npm must install the verified prebuilt wheel, with
--only-binary=:all: and an exact version/hash; a git dependency or source
archive still invokes the frontend build hook. A wheel is a Python package,
not a complete hosting upload configuration. See
release wheel preparation for the runtime proof,
artifact receipts and operator gates before selecting a published version.
Production notes:
A host serving directly from a checkout must run
uv run python scripts/build_dashboard.pyafter checkout/dependency installation and before starting or restarting the API. A host installing the built wheel already has the assets. CI verifies both paths.Configure every value through your host's secret manager;
.env.exampleis the non-secret contract. Never commit credentials or a database file.Set
BRAND_OS_ALLOWED_HOSTSto your public hostname and keepBRAND_OS_REQUIRE_HTTPS=truebehind TLS.The database must be durable. Do not ship a local SQLite file inside a container image.
OAuth state for the hosted MCP endpoint is stored in the same database.
The built-in password rate limit on
/oauth/authorizeis in memory and per process.
Walkthrough: docs/getting-started.md.
Documentation
Connecting MCP clients: Claude Code, Claude Desktop, Cursor, hosted OAuth
Configuration: every
BRANDMAN_*settingSeed packs: start a database with your own brands and house style
Deployment: Docker, TLS proxies, backups
Extending BrandMan: plugins, custom authentication, one database per workspace
Development
uv sync && uv run pytest
cd web && npm ci && npm test && npm run build # rebuilds brandman/static/appContributing
See CONTRIBUTING.md. Contributors sign a CLA.
License
Copyright (C) 2026 Austin Christensen.
GNU Affero General Public License v3.0. If you run a modified version as a network service, you must offer its source to the users of that service. The BrandMan name and logo are not covered by the license.
This server cannot be deployed
Maintenance
Related MCP Connectors
- QuallaaOAuthcom.quallaa
Talk to your public-facing AI from any MCP client — Claude, ChatGPT, Cursor, Cline, Windsurf.
Manage SRG+ hubs, channels, content, assets, users, and workspaces from any MCP-aware AI agent.
MCP server for your apps' tools and custom tools, plus hosted AI agents and approval-gated workflows
Human-input bridge for AI agents with voice-first answer links, MCP tools, and HTTP APIs.
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