boardroom-mcp
# šļø Boardroom MCP
**AI Governance-as-a-Service ā Model Context Protocol Server**
[](LICENSE)
[](https://www.npmjs.com/package/boardroom-mcp)
[](https://modelcontextprotocol.io)
> Give your AI agents a boardroom of advisors. Based on **Napoleon Hill's Mastermind Principle** ā the idea that coordinated minds produce intelligence no single mind can achieve ā digitized for AI agents.
Multi-advisor debate, institutional memory, trust scoring, and cognitive governance ā all running locally on your machine.
## š [Read the Full Documentation ā](https://salars.net/boardroom/docs)
Complete guide covering Quick Start ā Installation ā 5 Tools ā Use Cases ā Protocol Files ā Building Councils ā Debate Protocols ā Cognitive Drills ā Mind Versioning ā Architecture ā Full System.
---
## ā” Quick Start ā Pick Your Platform
> **Prerequisites:** Node.js 18+ must be installed. Check with `node --version`.
---
### š£ Claude Desktop
**Step 1:** Open your config file:
- **macOS:** `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Windows:** `%APPDATA%\Claude\claude_desktop_config.json`
**Step 2:** Paste this (create the file if it doesn't exist):
```json
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}
```
**Step 3:** Restart Claude Desktop completely (quit and reopen).
**Step 4: Test it** ā type this in the chat:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**Step 5: See what's available** ā type this in the chat:
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### š¢ Claude Code (CLI)
**Option A ā One command (recommended):**
```bash
claude mcp add boardroom -- npx -y boardroom-mcp
```
**Option B ā Config file:** Create `.mcp.json` in your project root:
```json
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}
```
**Test it** ā type this in Claude Code:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### šµ Cursor
**Step 1:** Open **Settings ā MCP** (or create `.cursor/mcp.json` in your project root)
**Step 2:** Add this server config:
```json
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}
```
**Step 3:** Restart Cursor.
**Test it** ā type in Cursor chat:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### š” Windsurf
**Step 1:** Open **Settings ā MCP** or create `.windsurf/mcp.json` in your project root.
**Step 2:** Add this server config:
```json
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}
```
**Step 3:** Restart Windsurf.
**Test it** ā type in Windsurf chat:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### š· VS Code (GitHub Copilot)
> Requires GitHub Copilot with agent mode enabled.
**Step 1:** Enable MCP: **Settings ā Copilot ā MCP** (toggle on).
**Step 2:** Create `.vscode/mcp.json` in your project root:
```json
{
"servers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}
```
> ā ļø **Note:** VS Code uses `"servers"` ā NOT `"mcpServers"`. This is different from all other platforms.
**Step 3:** Reload VS Code window (Ctrl+Shift+P ā "Reload Window").
**Test it** ā type in Copilot Chat (Agent mode):
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### ā« ChatGPT Desktop
> Requires ChatGPT Plus or Pro subscription.
**Step 1:** Open ChatGPT Desktop ā **Settings ā Developer ā Connectors**.
**Step 2:** Click "Add Custom MCP Server" and paste:
```json
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}
```
**Step 3:** Enable the "boardroom" connector in your chat.
**Test it** ā type in the chat:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### š OpenAI Codex CLI
**Option A ā One command (recommended):**
```bash
codex mcp add boardroom -- npx -y boardroom-mcp
```
**Option B ā Config file:** Add to `~/.codex/config.toml`:
```toml
[mcp_servers.boardroom]
type = "stdio"
command = "npx"
args = ["-y", "boardroom-mcp"]
```
**Test it** ā type in Codex CLI:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### š“ Antigravity
Create `.mcp.json` in your workspace root:
```json
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}
```
**Test it** ā type in the chat:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
### š¦ OpenClaw
> OpenClaw uses its **skills system** instead of MCP server configs.
**Step 1:** Clone and build the server:
```bash
git clone https://github.com/randysalars/boardroom-mcp.git
cd boardroom-mcp && npm install && npm run build
```
**Step 2:** Create the skill directory:
```bash
mkdir -p ~/.openclaw/skills/boardroom
```
**Step 3:** Create `~/.openclaw/skills/boardroom/SKILL.md`:
```markdown
---
name: boardroom
description: Boardroom Mastermind Council ā multi-advisor strategic analysis via MCP server.
metadata: {"clawdbot":{"emoji":"šļø","always":true,"requires":{"bins":["node"]},"primaryEnv":"BOARDROOM_ROOT"}}
---
# Boardroom MCP šļø
Multi-advisor strategic analysis. Run sessions via:
```bash
BOARDROOM_ROOT=~/.ai/boardroom node /path/to/boardroom-mcp/dist/index.js
```
Usage: "Board: Should I raise prices on my SaaS?"
```
**Step 4:** Add to `~/.openclaw/.env`:
```bash
BOARDROOM_ROOT=/path/to/your/.ai/boardroom
```
**Step 5:** Restart and verify:
```bash
systemctl --user restart openclaw-gateway.service
openclaw skills list | grep boardroom
# ā ready ā š¦ boardroom
```
**Test it** ā type in the chat:
```
Use the analyze tool with task: "Test ā is the Boardroom working?"
```
**See what's available:**
```
What Boardroom MCP tools do I have access to? List all 5 tools with a one-line description of each.
```
---
## ā
What Success Looks Like
When the test prompt works, you'll see output like:
```
# Boardroom Analysis
## Advisors Consulted
- **Warren Buffett** (Business Strategy): [their position]
- **Linus Torvalds** (Technology): [their position]
- **Marcus Aurelius** (Values & Ethics): [their position]
## Verdict
[synthesized recommendation]
## Recommended Actions
1. [action item]
2. [action item]
```
If you see this, **it's working.** Try a real question next:
```
Use the analyze tool with task: "Should I raise my SaaS price from $29 to $49?"
```
---
## š Quick Command Reference
Copy-paste these prompts into your AI chat to use each tool:
| What You Want | Prompt to Type |
|---------------|----------------|
| **Full analysis** | `Use the analyze tool with task: "Should I build feature X or Y?"` |
| **Risk check** | `Use the check_governance tool with task: "Deploy to production on Friday"` |
| **Search past decisions** | `Use the query_intelligence tool with query: "pricing strategy"` |
| **Trust assessment** | `Use the trust_lookup tool for entity: "Stripe" with context: "payment processing"` |
| **Log an outcome** | `Use the report_outcome tool with decision: "Raised prices 30%" and outcome: "Revenue up 22%"` |
| **List all tools** | `What Boardroom MCP tools do I have? List all 5 with descriptions.` |
---
## š¦ Alternative Installation Methods
```bash
# Option A: npx (used by MCP configs above ā no global install needed)
npx -y boardroom-mcp
# Option B: Global install
npm install -g boardroom-mcp
boardroom-mcp
# Option C: Clone and build (for development/contributing)
git clone https://github.com/randysalars/boardroom-mcp.git
cd boardroom-mcp && npm install && npm run build
```
> **Note:** If `npx` fails, use Option C (clone and build), then point your MCP config to the local build:
> ```json
> {
> "mcpServers": {
> "boardroom": {
> "command": "node",
> "args": ["/path/to/boardroom-mcp/dist/index.js"]
> }
> }
> }
> ```
---
## š§ 5 MCP Tools
| Tool | Purpose |
|------|---------|
| `analyze` | Full boardroom consultation with multi-advisor debate |
| `check_governance` | Task classification + severity routing |
| `query_intelligence` | Search LEDGER decisions + Wisdom Codex |
| `trust_lookup` | 6-dimension trust vector for any entity |
| `report_outcome` | Log outcomes for institutional memory |
ā [See detailed tool documentation with examples](https://salars.net/boardroom/docs#tools)
---
## šļø Architecture
```
Your AI Client (Claude, Cursor, Windsurf, VS Code, ChatGPT, Codex, Antigravity, OpenClaw)
ā MCP Protocol (STDIO)
ā Runs 100% on YOUR machine
ā¼
Boardroom MCP Server
ā
āāā demo/ ā Demo council (Buffett, Torvalds, Aurelius)
ā
ā¼
~/.ai/boardroom/ ā Full protocol files (optional upgrade)
āāā LEDGER.md ā Institutional memory
āāā BOARD_WISDOM.md ā Distilled principles
āāā mastermind/
āāā seats/ ā Advisor definitions
āāā councils/ ā Expert panels
āāā protocols/ ā Debate rules
```
**Zero cost.** No API keys. No cloud. No hosting. Your AI client does the LLM processing.
---
## šÆ What You Get
### Free (This Repo)
- ā
MCP server with 5 tools
- ā
Demo council (3 named advisors: Warren Buffett, Linus Torvalds, Marcus Aurelius)
- ā
MIT license
### Full System ([salars.net/boardroom](https://salars.net/boardroom))
- šļø 450+ named advisors with calibrated seat cards (Buffett, Torvalds, Aurelius...)
- šļø 38 expert councils (Tech, Business, Survival, Legal, Creative...)
- āļø 5 debate resolution types
- š§ 10 cognitive drills
- ā³ Mind Versioning (Young Jobs vs Late Jobs)
- š„ Prometheus Protocol (forge new domains on the fly)
- šļø Meta-Observer (real-time bias detection)
- š 69+ LEDGER decisions as precedent library
- š 113+ Wisdom Codex entries
- šÆ Smart Router (auto-detects council + severity)
---
## āļø Environment Variables
| Variable | Default | Description |
|----------|---------|-------------|
| `BOARDROOM_ROOT` | `~/.ai/boardroom` | Path to your full protocol files directory |
| `BOARDROOM_TRUST_PATH` | `~/.boardroom/trust-oracle.json` | Path to trust oracle data file |
---
## š Troubleshooting
### The AI ignores my prompt and doesn't use the tool
**This is the #1 issue.** It means the MCP server isn't loaded. Fix it:
1. **Did you restart?** Every platform requires a restart after editing the config. Quit completely and reopen.
2. **Is the config in the right file?** Double-check the file path for your platform (see Quick Start above).
3. **Is the JSON valid?** No trailing commas, no comments. Use [jsonlint.com](https://jsonlint.com) to validate.
4. **Is Node.js 18+ installed?** Run `node --version` in your terminal. Must be 18.0.0 or higher.
5. **VS Code users:** You need `"servers"` not `"mcpServers"` ā VS Code uses a different format.
### The AI says "boardroom-mcp not found" or npx fails
```bash
# Verify the package exists
npm view boardroom-mcp version
# If that works but npx doesn't, clear cache:
npx clear-npx-cache
npx -y boardroom-mcp
# Nuclear option ā install globally:
npm install -g boardroom-mcp
```
Then update your config to use the global install:
```json
{
"mcpServers": {
"boardroom": {
"command": "boardroom-mcp"
}
}
}
```
### "No advisors found" in the output
The demo council file isn't being found. This means the package installed but can't find `demo/seats.md`.
```bash
# Check if the demo file exists in the package
npx -y boardroom-mcp --help 2>/dev/null
ls $(npm root -g)/boardroom-mcp/demo/
```
If the demo directory is missing, reinstall: `npm install -g boardroom-mcp`
### ENOENT errors
You're pointing at a `BOARDROOM_ROOT` directory that doesn't exist:
```bash
# Check what path it's looking for
echo $BOARDROOM_ROOT
# Create it or unset the variable:
unset BOARDROOM_ROOT # falls back to demo council
```
### Tools appear but return errors
```bash
# Test the server directly in your terminal:
npx -y boardroom-mcp
# If it starts without errors, the MCP server works.
# The issue is in your AI client's connection to it.
# Try removing and re-adding the MCP config.
```
### Claude Code specific: "MCP server failed to start"
```bash
# Remove and re-add:
claude mcp remove boardroom
claude mcp add boardroom -- npx -y boardroom-mcp
# Verify it's registered:
claude mcp list
```
### Permission errors on macOS
```bash
# If npx can't write to the cache:
sudo chown -R $(whoami) ~/.npm
npm cache clean --force
```
### Platform-specific config cheat sheet
| Platform | Config File | Key Name | Restart Method |
|----------|------------|----------|----------------|
| Claude Desktop | `claude_desktop_config.json` | `mcpServers` | Quit + reopen app |
| Claude Code | `.mcp.json` or `claude mcp add` | `mcpServers` | Auto-reloads |
| Cursor | `.cursor/mcp.json` or Settings ā MCP | `mcpServers` | Restart Cursor |
| Windsurf | `.windsurf/mcp.json` or Settings ā MCP | `mcpServers` | Restart Windsurf |
| VS Code | `.vscode/mcp.json` | ā ļø `servers` | Reload Window |
| ChatGPT Desktop | Settings ā Developer ā Connectors | `mcpServers` | Toggle connector |
| Codex CLI | `~/.codex/config.toml` or `codex mcp add` | `mcp_servers` (TOML) | Auto-reloads |
| Antigravity | `.mcp.json` | `mcpServers` | Auto-reloads |
| OpenClaw | `~/.openclaw/skills/boardroom/SKILL.md` | Skills system | Restart gateway |
---
## š¬ Stay in the Loop
- š **[Landing Page](https://salars.net/boardroom)** ā Feature overview + pricing
- š **[Documentation](https://salars.net/boardroom/docs)** ā Complete free ā advanced guide
- š§ **[Get Full Access ā $29](https://salars.net/boardroom/checkout)** ā 450+ advisors, 38 councils, lifetime access
- š¦ **[@SalarsNet](https://x.com/salaborsa)** ā Tips, demos, and announcements
---
## š¤ Contributing
PRs welcome! Areas we'd love help with:
- Additional demo advisors
- New cognitive drill templates
- Documentation improvements
- Bug fixes
---
## š License
[MIT](LICENSE) ā Built by [SalarsNet](https://salars.net)
TDQS
Scored across 5 tools
Each tool targets a distinct action: classification, search, trust lookup, outcome reporting, and full consultation. The only minor overlap is between query_intelligence and analyze, as both access institutional memory, but their purposes are clearly differentiated by analysis' routing to advisors.
Tool names mix verb_noun patterns (check_governance, query_intelligence, report_outcome) with a noun_verb compound (trust_lookup) and a single verb (analyze). This is readable but not fully consistent, making the pattern less predictable than it could be.
Five tools is well-scoped for a governance/consultation server, covering classification, memory search, trust evaluation, outcome feedback, and full analysis without redundancy. Each tool earns its place in the workflow.
The core lifecycle is covered: classify, analyze, query, report, and trust lookup are present, with feedback loops for learning. Minor gaps exist (e.g., no direct tool for editing governance protocols), but agents can work around this with the existing tools.