Boardroom MCP Documentation
From zero to a fully governed AI agent in 5 minutes. This guide takes you from the free demo council all the way through advanced cognitive protocols like Mind Versioning and the Prometheus Protocol.
Quick Start
FREEGet your first boardroom consultation in under 2 minutes. The free server ships with a demo council of 3 named advisors (Warren Buffett, Linus Torvalds, Marcus Aurelius) β no API keys, no accounts, no configuration.
1. Add to your MCP client
Open your Claude Desktop config (or Cursor, Windsurf, etc.) and add the boardroom server:
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}2. Ask your agent a question
Now just ask your AI agent to consult the boardroom:
"Board: Should I build a mobile app or a progressive web app
for my new SaaS product?"3. What you get back
The boardroom returns structured analysis from multiple advisors β each with a distinct perspective, confidence score, and recommendation. The demo council includes:
Warren Buffett
Business strategy, competitive moats, and long-term value
Linus Torvalds
Technology architecture, simplicity, and maintainability
Marcus Aurelius
Values alignment, ethical judgment, and Stoic wisdom
Installation
FREEFollow the step-by-step guide for your AI tool below. No coding experience required β just copy, paste, and restart.
β‘ Before you start β check Node.js
Boardroom MCP needs Node.js 18 or higher. Open a terminal and run:
node --versionYou should see something like v22.12.0. If you see an error or a version below 18, install Node.js from nodejs.org (choose the LTS version).
Choose your AI tool:
π£Claude Desktop βMOST POPULAR
Step 1: Find the config file
macOS: Open Finder β Go β Go to Folder β paste: ~/Library/Application Support/Claude/
Windows: Press Win+R β paste: %APPDATA%\Claude\
Linux: ~/.config/Claude/
Step 2: Edit claude_desktop_config.json
Open (or create) claude_desktop_config.json and paste this entire block:
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}π‘ If the file already has other servers, just add the "boardroom": {...} block inside the existing mcpServers object (don't forget a comma after the previous entry).
Step 3: Restart Claude Desktop
Fully quit Claude Desktop (not just close the window β right-click the dock/taskbar icon β Quit) and reopen it.
Step 4: Test it!
Type this into Claude:
Use the analyze tool with task: "Test β is the Boardroom working?"β If you see a response with advisor names and recommendations, you're all set!
β¨οΈClaude Code (CLI) β
One command β that's it:
claude mcp add boardroom -- npx -y boardroom-mcpThis registers the Boardroom as an MCP server. Now just ask Claude Code:
Use the analyze tool with task: "Test β is the Boardroom working?"π±οΈCursor β
Step 1: Create the config file
In your project's root folder, create a file called .cursor/mcp.json and paste:
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}Step 2: Restart Cursor
Close and reopen Cursor, or press Cmd+Shift+P β "Reload Window".
Step 3: Test in Agent mode
Open the AI chat panel (Cmd+L), switch to Agent mode, and type your question.
πVS Code β(GitHub Copilot)
Step 1: Enable MCP in Copilot
Go to Settings β Extensions β Copilot and enable MCP support.
Step 2: Create the config file
Create .vscode/mcp.json in your project root. β οΈ Note: VS Code uses servers, not mcpServers.
{
"servers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}Step 3: Reload and test
Press Cmd+Shift+P β "Reload Window". Then open Copilot Chat in Agent mode and ask your question.
πWindsurf β
Step 1: Open MCP settings
Go to Settings β MCP and click "Add Server".
Step 2: Add the config
Paste this JSON:
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}Step 3: Restart and test
Restart Windsurf and ask Cascade a question to verify.
π€ChatGPT Desktop βPlus/Pro required
Step 1: Open Connectors
In ChatGPT Desktop, go to Settings β Developer β Connectors.
Step 2: Add MCP server
Click "Add Connector" β choose MCP β set command to npx with args -y boardroom-mcp.
Step 3: Restart and test
Restart ChatGPT Desktop and ask a question.
One command:
codex mcp add boardroom -- npx -y boardroom-mcpπAntigravity β
Add to your config:
Create or edit .mcp.json in your workspace root:
{
"mcpServers": {
"boardroom": {
"command": "npx",
"args": ["-y", "boardroom-mcp"]
}
}
}π¦OpenClaw β
Step 1: Clone and build
OpenClaw uses its skills system instead of MCP server configs. First, clone and build the server:
git clone https://github.com/randysalars/boardroom-mcp.git
cd boardroom-mcp && npm install && npm run buildStep 2: Create the skill directory
mkdir -p ~/.openclaw/skills/boardroomStep 3: Create the skill file
Create ~/.openclaw/skills/boardroom/SKILL.md with this content:
---
name: boardroom
description: Boardroom Mastermind Council β multi-advisor strategic analysis via MCP server.
metadata: {"clawdbot":{"emoji":"ποΈ","always":true,"requires":{"bins":["node"]},"primaryEnv":"BOARDROOM_ROOT"}}
---
# Boardroom MCP ποΈ
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 environment variable
Add to ~/.openclaw/.env:
BOARDROOM_ROOT=/path/to/your/.ai/boardroomStep 5: Restart and verify
systemctl --user restart openclaw-gateway.service
openclaw skills list | grep boardroomYou should see: β ready β π¦ boardroom
π§ Alternative: Build from source
If npx doesn't work or you want to modify the code, you can clone and build from GitHub:
git clone https://github.com/randysalars/boardroom-mcp.git
cd boardroom-mcp
npm install
npm run build
npm startThen use the full path to the built file as the command in your MCP config instead of npx.
Environment Variables (Optional)
These are only needed if you're using the full protocol files (paid tier). The free demo works with zero configuration.
| Variable | Default | Description |
|---|---|---|
| BOARDROOM_ROOT | ~/.ai/boardroom | Path to your protocol files directory (seat cards, LEDGER, Wisdom Codex) |
| BOARDROOM_TRUST_PATH | ~/.boardroom/trust-oracle.json | Path to trust oracle data file |
The 5 Tools
FREEThe MCP server exposes 5 tools that your AI agent can call. Each tool handles a different aspect of AI governance β from multi-advisor debate to trust scoring.
analyze()
ConsultationFull boardroom consultation with multi-advisor synthesis. Routes your question to relevant advisors, loads their philosophies and decision criteria, searches LEDGER precedents and Wisdom Codex, and returns a structured markdown analysis with mandatory tension between opposing viewpoints.
Parameters
taskstringβ The decision, question, or task to analyze// Your AI agent calls this automatically when you say:
"Board: Should we migrate from REST to GraphQL?"
// It returns structured markdown:
# Boardroom Analysis
## Classification: technology
## Advisors Consulted
- **Linus Torvalds** β Technology architecture, simplicity
- **Warren Buffett** β Business strategy, competitive moats
- **Marcus Aurelius** β Values alignment, ethical judgment
## LEDGER Precedents
(matching past decisions)
## Wisdom Codex
(relevant distilled principles)
## Mandatory Tension
- **Torvalds:** Keep it simple, REST works fine
- **Buffett:** What creates the most long-term value?check_governance()
ClassificationClassifies a proposed task or action and provides governance routing β which councils should review it, what risk level it warrants, and any constitutional constraints. Fast classification without running a full boardroom session.
Parameters
taskstringβ The proposed task or action to classify// Classify before acting:
"Use check_governance: Delete the production database backup"
// Returns markdown classification:
# Governance Check
**Decision Type:** technology
**Risk Level:** π΄ Critical
**Recommended Councils:** Technology, Risk
**Constitutional Flags:** Requires explicit human approval
**Recommended Action:** Full boardroom session before proceedingquery_intelligence()
KnowledgeSearches the LEDGER (past decisions) and the Wisdom Codex (distilled principles) for relevant precedents. This gives your agent institutional memory β it remembers what was decided before and why.
Parameters
querystringβ Search query β topic, keyword, or questionlimitnumberβ Max results to return (default: 10)// Search for past decisions:
"Use query_intelligence: pricing strategy"
// Returns matching LEDGER entries + wisdom:
# Intelligence Report
## LEDGER Matches (2 found)
- 2026-01-15: Adopted value-based pricing over cost-plus...
- 2026-02-01: Raised prices 30%, churn stayed flat...
## Wisdom Codex Matches (1 found)
- Price anchors: always show the most expensive option first...trust_lookup()
TrustReturns a 6-dimension trust vector for any entity β AI agent, tool, vendor, or platform. Dimensions: reliability, honesty, follow-through, outcome quality, stability, and risk profile. New entities return an "unknown" profile with bootstrap instructions.
Parameters
entitystringβ The entity to look up β agent name, tool, vendor, or platformcontextstringβ Optional context about how you are using this entity// Look up trust for a vendor:
"Use trust_lookup for entity: Stripe, context: payment processing"
// Returns 6-dimension trust vector:
# Trust Lookup: Stripe
## 6-Dimension Trust Vector
| Dimension | Score | Weight |
|------------------|-------|--------|
| Reliability | 95% | 25% |
| Honesty | 92% | 20% |
| Follow-Through | 88% | 20% |
| Outcome Quality | 90% | 15% |
| Stability | 85% | 10% |
| Risk Profile | 80% | 10% |
**Composite Score:** 89.5%
**Recommendation:** β
TRUSTreport_outcome()
LearningLogs the outcome of a past decision to the LEDGER. Creates institutional memory β your boardroom gets smarter over time as it learns from results. Returns a warning if the outcome could not be persisted to disk.
Parameters
taskstringβ The original task or decisionoutcomestringβ What actually happened β result, success/failure, learningsfollowedRecommendationbooleanβ Whether the Boardroom recommendation was followed (default: true)// Log what happened after a decision:
"Use report_outcome: task 'Migrated to GraphQL',
outcome 'Reduced API calls by 60% but increased complexity'"
// Returns confirmation:
# Outcome Recorded
β
Decision outcome has been logged to the Knowledge Flywheel.
**Task:** Migrated to GraphQL
**Outcome:** Reduced API calls by 60%, but increased complexity
**Followed Recommendation:** Yes
**Persisted:** Yes β
Use Cases
FREEThe Boardroom works for any decision β from quick tech choices to high-stakes strategy. Here are real-world examples with the exact prompts to use.
ποΈ Architecture Decisions
βShould I build a mobile app or PWA for my SaaS?β
analyzeUse the analyze tool: "Should I build a native mobile app or a progressive web app for my B2B SaaS product? We have 2 developers and need to ship in 3 months."Why it works: Buffett evaluates long-term competitive value, Torvalds assesses technical feasibility and maintenance burden, Aurelius asks if you're reacting to fear of missing out or acting from real user demand.
βMonolith vs microservices for a growing startup?β
analyzeUse the analyze tool: "We have 50K users and growing. Our monolith is getting hard to deploy. Should we start breaking it into microservices?"Why it works: The boardroom prevents premature optimization β Torvalds will push back hard on unnecessary complexity while Buffett evaluates the cost of engineering time vs scaling risk.
π° Business Strategy
βShould I raise prices by 50%?β
analyzeUse the analyze tool: "I'm considering raising our SaaS price from $29/mo to $49/mo. We have 200 paying customers and low churn. Is this the right move?"Why it works: Buffett applies margin-of-safety thinking to pricing, Aurelius challenges whether you're motivated by greed or genuine value delivery.
βShould I quit my job for my side project?β
analyzeUse the analyze tool: "My side project makes $4K/mo. My job pays $12K/mo. I have 8 months of savings. Should I go full-time on the side project?"Why it works: This is where multi-advisor debate shines β the advisors will disagree and surface risks you haven't considered.
π‘οΈ Risk Assessment
βIs this deployment safe?β
check_governanceUse the check_governance tool: "Deploy new payment processing system to production on a Friday evening"Why it works: Instant severity classification β this will flag as high-risk and recommend waiting for Monday. No debate needed, just fast classification.
βShould I give an AI agent database access?β
check_governanceUse the check_governance tool: "Grant our AI coding assistant read-write access to the production database for automated migrations"Why it works: Constitutional checks will flag this as requiring explicit human approval, with risk factors around data integrity and blast radius.
π€ Trust & Evaluation
βCan I trust this vendor?β
trust_lookupUse the trust_lookup tool for entity: "Stripe" with context: "payment processing for our SaaS"Why it works: Returns a 6-dimension trust vector (reliability, honesty, follow-through, outcome quality, stability, risk profile) with a composite score and recommendation.
βShould I hire this freelancer?β
trust_lookupUse the trust_lookup tool for entity: "A freelance developer with 5-star reviews but no portfolio and a 2-month-old profile"Why it works: The trust oracle will flag low transparency and missing track record despite surface-level signals.
π Institutional Memory
βWhat did we decide about pricing before?β
query_intelligenceUse the query_intelligence tool: "pricing strategy decisions"Why it works: Searches your LEDGER for past pricing decisions and the Wisdom Codex for distilled pricing principles β so you don't repeat past mistakes.
βLog what actually happenedβ
report_outcomeUse the report_outcome tool: task "Raised prices 30%", outcome "Revenue up 22%, churn stayed flat at 3%"Why it works: Creates institutional memory β your boardroom gets smarter over time. Next time someone asks about pricing, this outcome is available as a precedent.
π― Everyday Decisions
βWhich feature should I build next?β
analyzeUse the analyze tool: "I have 3 feature requests: (1) dark mode, (2) API access, (3) team collaboration. We can only build one this quarter. Which one?"Why it works: The boardroom forces structured prioritization instead of gut feeling β each advisor applies their domain lens to the same options.
βShould I open-source my project?β
analyzeUse the analyze tool: "Should I open-source my developer tool? It has 500 users and makes $2K/mo. I'm worried about clones but excited about community contributions."Why it works: Buffett evaluates moat erosion, Torvalds champions open-source benefits, Aurelius asks what you'd be proud of regardless of outcome.
π‘ Pro tip: Chain tools together
Use check_governance first for quick severity classification, then query_intelligence to pull relevant precedents, then analyze for the full boardroom debate. After you act on the advice, use report_outcome to log what happened.
π¬ Example: Full Boardroom Session
Here's what you actually see when you ask the Boardroom a real question. This is the kind of output the analyze tool returns β multiple advisors with distinct philosophies, structured debate, and actionable synthesis.
Your prompt:
Board: My side project makes $4K/mo. My job pays $12K/mo. I have 8 months of savings. Should I go full-time on the side project?What the Boardroom returns:
# ποΈ Boardroom Analysis
## Classification
**Decision Type:** business-strategy
**Severity:** π΄ Critical (life-changing, irreversible in the short term)
**Councils Invoked:** Business Strategy, Risk Assessment, Values Alignment
---
## π Advisors Consulted
### Warren Buffett β Business Strategy & Competitive Moats
> **Core philosophy:** Never risk what you have and need for what you don't have and don't need.
>
> **Position: PROCEED WITH CAUTION** β οΈ
>
> "Your side project is growing β $4K/month is real signal. But here's
> what I'd want to know: What's the trajectory? If it took 12 months
> to reach $4K, that's very different from 3 months. I'd want to see
> 3 consecutive months of growth before making the leap.
>
> **The math matters:** $8K/mo gap Γ 8 months = $64K of runway without
> growth. That's not a safety margin, that's a countdown timer.
> I'd want 18 months of runway before I'd call it safe.
>
> **My recommendation:** Don't quit. Negotiate a 4-day work week or
> contract your current role. Get the side project to $8K/mo first."
### Linus Torvalds β Technology & Execution
> **Core philosophy:** Talk is cheap. Show me the code.
>
> **Position: LEAN TOWARD GOING** π’
>
> "Stop overthinking. The real question isn't the money β it's whether
> this thing has technical legs. At $4K/mo you've proved market fit.
> What's holding the growth back β is it YOUR time?
>
> If the bottleneck is that you can't ship fast enough because of
> the day job, then staying employed is actively killing the project.
> Every day you're NOT working on it is a day a competitor could
> eat your lunch.
>
> **But:** Make sure you own the IP cleanly. Check your employment
> contract for moonlighting clauses and IP assignment."
### Marcus Aurelius β Values & Philosophical Alignment
> **Core philosophy:** The impediment to action advances action. What stands in the way becomes the way.
>
> **Position: ASK A DEEPER QUESTION** π€
>
> "Before you solve the logistics, answer this: If the side project
> failed completely in 6 months and you had to find a new job β would
> you regret trying? Or would you regret NOT trying?
>
> Fear of financial loss is rational. But there is another fear
> hiding behind it: the fear of discovering that your project
> ISN'T as good as you hope. Staying employed lets you avoid that
> reckoning indefinitely.
>
> **The Stoic test:** Imagine it's 5 years from now. Which decision
> will you respect yourself for making? That's your answer."
---
## βοΈ Mandatory Tension
| Advisor | Position | Key Risk They See |
|---------|----------|-------------------|
| Buffett | β οΈ Wait | Insufficient runway, no growth guarantee |
| Torvalds | π’ Go | Day job is the bottleneck killing growth |
| Aurelius | π€ Deeper | Decision is about identity, not just money |
**The core disagreement:** Buffett sees this as a financial optimization problem
(wait for more data). Torvalds sees it as an execution problem (the job is the
obstacle). Aurelius reframes entirely β this is a question about who you want to be.
---
## π LEDGER Precedents (1 match)
- **2026-01-20:** "Whether to pursue full-time contracting vs employment"
β Outcome: Took contract, revenue doubled in 60 days. Key learning:
the flexibility itself was the competitive advantage.
## π Wisdom Codex (2 matches)
- *"Irreversible decisions deserve 10x the analysis of reversible ones.
Quitting a job is semi-reversible β you can get another job, but
not the same one."*
- *"Revenue β profit. $4K/mo with $1K in costs and no benefits is $3K.
Compare that to $12K + health insurance + 401K match."*
---
## π― CEO Synthesis
**Recommended Path:** Hybrid transition over 90 days.
1. **Immediately:** Negotiate reduced hours or 4-day week at current job
2. **Next 30 days:** Validate growth trajectory at increased effort
3. **Day 60:** If side project hits $6K/mo, give notice
4. **Day 90:** Full transition with 6+ months of true runway
**Why this path:** It resolves Buffett's runway concern, tests Torvalds'
bottleneck theory without burning bridges, and gives you Aurelius' answer
through action rather than analysis.
**Risk watchout:** If your employer says no to reduced hours, that IS your
answer β they've made the decision for you.Note: This is a representative demo-mode output with 3 advisors. The full protocol files (paid tier) unlock 450+ advisors across 38 expert councils β each with unique philosophies, decision criteria, veto power, and advice styles. Industry-specific advisors are routed automatically based on your question.
Quick Command Reference
FREECopy-paste these prompts into your AI chat to use each tool. These work in any MCP-compatible client.
| 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 task: "Raised prices 30%" and outcome: "Revenue up 22%" |
| List all tools | What Boardroom MCP tools do I have? List all 5 with descriptions. |
| Test installation | Use the analyze tool with task: "Test β is the Boardroom working?" |
Troubleshooting
FREEThe AI ignores my prompt and doesn't use the tool
This is the #1 issue β it means the MCP server isn't loaded.
- Did you restart? Every platform requires a restart after editing the config.
- Is the config in the right file? Double-check the file path for your platform.
- Is the JSON valid? No trailing commas, no comments. Use jsonlint.com to validate.
- Is Node.js 18+ installed? Run node --version in your terminal.
- VS Code users: You need "servers" not "mcpServers" β VS Code uses a different format.
"boardroom-mcp not found" or npx fails
The npm package isn't accessible.
- Run: npm view boardroom-mcp version β to verify the package exists.
- Clear cache: npx clear-npx-cache && npx -y boardroom-mcp
- Nuclear option: npm install -g boardroom-mcp β then use "boardroom-mcp" as the command.
- If all else fails: clone the repo and build from source (see Alternative Installation).
"No advisors found" in the output
The package installed but can't find the demo council files.
- Check if demo/seats.md exists in the installed package.
- Reinstall: npm install -g boardroom-mcp
- If using BOARDROOM_ROOT, ensure the path exists and contains protocol files.
ENOENT errors
You're pointing at a BOARDROOM_ROOT directory that doesn't exist.
- Check your path: echo $BOARDROOM_ROOT
- Unset the variable to fall back to demo: unset BOARDROOM_ROOT
- Or create the directory the variable points to.
Claude Code: "MCP server failed to start"
The MCP registration is corrupted or outdated.
- Remove and re-add: claude mcp remove boardroom
- Then: claude mcp add boardroom -- npx -y boardroom-mcp
- Verify: claude mcp list β should show "boardroom" in the list.
Permission errors on macOS
npx can't write to the npm cache directory.
- Fix ownership: sudo chown -R $(whoami) ~/.npm
- Clear cache: npm cache clean --force
- Try again: npx -y boardroom-mcp
Platform Config Cheat Sheet
| Platform | Config File | Key Name | Restart Method |
|---|---|---|---|
| Claude Desktop | claude_desktop_config.json | mcpServers | Quit + reopen app |
| Claude Code | .mcp.json or claude mcp add | mcpServers | Auto-reloads |
| Cursor | .cursor/mcp.json or Settings β MCP | mcpServers | Restart Cursor |
| Windsurf | .windsurf/mcp.json or Settings β MCP | mcpServers | Restart Windsurf |
| VS Code | .vscode/mcp.json | β οΈ servers | Reload Window |
| ChatGPT Desktop | Settings β Developer β Connectors | mcpServers | Toggle connector |
| Codex CLI | ~/.codex/config.toml or codex mcp add | mcp_servers (TOML) | Auto-reloads |
| Antigravity | .mcp.json | mcpServers | Auto-reloads |
| OpenClaw | ~/.openclaw/skills/boardroom/SKILL.md | Skills system | Restart gateway |
Protocol Files
COREThe MCP server is the engine. Protocol files are the fuel. They define who your advisors are, how they debate, and what your boardroom remembers.
Directory Structure
.ai/boardroom/
βββ LEDGER.md # Decision log (institutional memory)
βββ BOARD_WISDOM.md # Distilled principles from past sessions
βββ mastermind/
β βββ SYSTEM_PROMPT.md # Core operating rules for the boardroom
β βββ RULE_MATRIX.md # Which rules fire at each severity
β βββ COGNITIVE_DOSSIERS.md # Deep profiles for each advisor
β βββ SIGNATURE_QUESTIONS.md # Each advisor's unique probing questions
β βββ CONVERSATION_TEMPLATE.md # How debate sessions are structured
β βββ seats/ # Individual advisor definitions
β β βββ 01-ceo.md
β β βββ 02-product.md
β β βββ 03-marketing.md
β β βββ ...
β βββ councils/ # Specialized expert panels
β βββ tech/
β βββ survival/
β βββ legal/
β βββ ...How the server finds them
The MCP server looks for protocol files in this order:
BOARDROOM_ROOTenvironment variable (if set)SALARSNET_ROOT/.ai/boardroom(if set)$HOME/Projects/salarsu/.ai/boardroom(default)- Falls back to built-in demo council (Buffett, Torvalds, Aurelius)
π‘ Want the full protocol files?
The open-source repo includes a demo council. The full system with 450+ calibrated advisors, 38 councils, cognitive dossiers, and debate protocols is available at salars.net/boardroom.
Building Your Own Councils
COREYou don't have to use pre-built advisors. Create your own councils tailored to your domain.
Anatomy of a Seat Card
Each advisor is defined by a seat card β a markdown file that describes their personality, expertise, decision criteria, and communication style.
# Seat: Chief Security Officer
## Role
Security & Risk Assessment Lead
## Core Philosophy
"Every system is as secure as its weakest link.
Assume breach. Design for resilience."
## Decision Criteria
1. Does this introduce new attack surface?
2. Does this follow the principle of least privilege?
3. Is there a rollback plan if this is compromised?
4. Have we considered supply chain risks?
## Veto Power
Can VETO any action that:
- Exposes PII without encryption
- Removes authentication from an endpoint
- Introduces unaudited third-party dependencies
## Signature Questions
- "What happens if this is compromised at 3 AM?"
- "Who has access, and should they?"
- "What does the blast radius look like?"
## Advice Style
Direct. Data-driven. Uses threat modeling frameworks.
Never says "it depends" without specifying conditions.Creating a Council
Group related advisors into a council folder:
.ai/boardroom/mastermind/councils/security/
βββ council-config.md # Council metadata + routing rules
βββ seats/
β βββ cso.md # Chief Security Officer
β βββ red-team.md # Red Team Lead
β βββ compliance.md # Compliance Expert
β βββ forensics.md # Digital Forensics Analyst# Security & Risk Council
## Routing Keywords
security, authentication, authorization, encryption,
vulnerability, compliance, GDPR, SOC2, penetration, audit
## Default Severity
standard (elevated to critical for auth/encryption topics)
## Members
- CSO (Chair)
- Red Team Lead
- Compliance Expert
- Digital Forensics Analyst
## Resolution Protocol
Unanimous on security vetoes. Majority on recommendations.Debate Protocols
ADVANCEDReal boardrooms don't just give opinions β they argue until something true emerges. The Boardroom MCP supports 5 resolution types for structured intellectual combat.
Consensus
All advisors converge on a shared position. Used when alignment matters more than speed.
Best for: Values decisions, mission-critical choices
Majority Vote
Simple majority carries. Dissenting opinions are preserved and logged.
Best for: Tactical decisions, time-sensitive choices
Dialectic Synthesis
Thesis β Antithesis β Synthesis. Forces opposing views to produce a new, higher-order insight.
Best for: Complex strategy, paradoxical situations
Adversarial
No resolution sought. Raw tension preserved as data. Used when disagreement IS the insight.
Best for: Risk assessment, stress testing assumptions
Omega Synthesis
CEO/Integrator synthesizes all positions into a final decision with explicit tradeoffs named.
Best for: Default for standard/critical severity sessions
Conversation Mode (Rule 12)
For Standard (π‘) and Critical (π΄) sessions, advisors don't give monologues β they debate each other. The conversation follows this structure:
1. Opening Positions
Each active advisor gives a raw 2-3 sentence gut reaction
2. Interactive Dialogue
Advisors respond to EACH OTHER:
**[Member A]**: "Here's why I disagree with B's position..."
**[Member B]**: "That ignores the data showing..."
**[Member A] shifts position**: "Actually, if we combine..."
3. Emergent Insights
Ideas that ONLY emerged from the interaction itself
4. Unresolved Tensions
Disagreements preserved as data β not forced into consensusCognitive Drills
ADVANCED10 cognitive exercises to sharpen your boardroom's thinking. Use Board: Drill [#] to invoke any drill.
Pre-Mortem
Assume the project failed. Why?
Inversion
How would we guarantee failure?
Steel Man
Make the strongest case for the opposing view
Red Team
Attack your own plan as an adversary would
Second-Order
What are the consequences of the consequences?
Regret Minimization
Which choice minimizes regret at age 80?
Opportunity Cost
What are we NOT doing by choosing this?
Boundary Push
What if we 10x'd this? What if we did 1/10th?
Historical Parallel
When has a similar situation played out before?
Assumption Audit
List every assumption. Test each one.
Mind Versioning & Prometheus Protocol
ADVANCEDMind Versioning
Invoke advisors at different points in their lives. Young Steve Jobs (1984, hungry rebel) gives different advice than Late-Stage Jobs (2010, product philosopher).
"Board: I want to hear from Young Buffett (1960s,
aggressive value hunter) AND Late Buffett (2020s,
quality compounder) on this acquisition."
// The engine invokes two versions of the same advisor
// with different calibration profiles, creating temporal
// debate between past-self and future-self.The Prometheus Protocol π₯
When no existing council covers a topic, forge a new domain on the fly. The Prometheus Protocol dynamically creates temporary advisors calibrated for the specific question.
"Board: I need expertise on quantum error correction
for my startup's hardware. None of your councils
cover quantum computing."
// Prometheus Protocol activates:
// 1. Identifies knowledge gap
// 2. Forges 3-5 temporary advisors calibrated for the domain
// 3. Runs a single-session debate
// 4. Advisor profiles are NOT persisted (fire-and-forget)Meta-Observer ποΈ
A silent advisor that watches every session for cognitive bias. It flags:
- Groupthink (all advisors converging too quickly)
- Anchoring (first speaker disproportionately influences the group)
- Confirmation bias (ignoring disconfirming evidence)
- Availability bias (overweighting recent/memorable events)
- Sunk cost fallacy (justifying past investments)
Architecture
REFERENCEThe Boardroom MCP follows a local-first, zero-dependency architecture.
βββββββββββββββββββββββββββββββββββββββββββββββββββ
β Your AI Client β
β (Claude, Cursor, Windsurf, OpenClaw, etc.) β
βββββββββββββββββββ¬ββββββββββββββββββββββββββββββββ
β MCP Protocol (STDIO)
β (runs 100% on YOUR machine)
βββββββββββββββββββΌββββββββββββββββββββββββββββββββ
β Boardroom MCP Server β
β ββββββββββββ¬βββββββββββ¬βββββββββββ¬ββββββββββββ β
β β analyze βgovernanceβ intel β trust β β
β β β β β β β
β ββββββ¬ββββββ΄βββββ¬ββββββ΄βββββ¬βββββ΄ββββββ¬ββββββ β
β β β β β β
β ββββββΌβββββββββββΌβββββββββββΌβββββββββββΌββββββ β
β β File System Reader β β
β β (reads .ai/boardroom/ directory) β β
β ββββββββββββββββββββββββββββββββββββββββββββββ β
βββββββββββββββββββββββββββββββββββββββββββββββββββ
β
βββββββββββββΌβββββββββββββ
β .ai/boardroom/ β
β βββ LEDGER.md β β Institutional memory
β βββ BOARD_WISDOM.md β β Distilled principles
β βββ mastermind/ β β Advisor definitions
β βββ seats/ β
β βββ councils/ β
β βββ protocols/ β
ββββββββββββββββββββββββββKey Properties
Local-First
Everything runs on your machine. No network calls. No API keys.
Zero Cost
No hosting. No bandwidth. Your AI client does the LLM processing.
File-Based
Protocol files are markdown. Edit with any text editor.
Composable
Mix pre-built councils with your own custom advisors.
OpenClaw Deep Integration
INTEGRATIONThe Boardroom MCP plugs directly into OpenClaw's autonomous agent infrastructure β 10 deep integration points that turn every cron job, skill, and safety gate into a boardroom-aware decision node.
Boardroom Sessions
MCP-first analysis with named advisors, automatic fallback to generic 7-seat simulation.
Governance Gate
Pre-execution risk check for cron jobs. Routine tasks auto-approve; critical ones pause for human review.
AUREUS Idea Stress-Test
High-impact monetization ideas are routed through boardroom analysis before execution.
A2A Trust Oracle
Cross-references trust profiles against the boardroom's 6-dimension trust vector.
Sentinel Watcher Hook
Anomalies from Sentinel auto-route through boardroom governance for risk classification.
Decision Queue
Queues boardroom decisions during heartbeat cycles. Routine actions auto-approve; critical ones wait.
Course β Board Routing
Course analysis uses MCP named advisors first, falls back to Gemini API if unavailable.
Decision Queue Processing
Batch processes pending decisions with configurable auto-approve thresholds.
Kill Switch Governance
Freeze events route through boardroom for analysis and outcome logging.
Narrative Guard
When brand drift score drops below 60, Values & Alignment Council provides correction recommendations.
How It Works
Every integration follows the same resilient pattern:
1. Try MCP First
Named advisors, protocol files, calibrated philosophies
2. Graceful Fallback
If MCP unavailable, existing behavior continues uninterrupted
3. Learn & Report
Outcomes logged to boardroom memory for continuous learning
# 1. Clone the protocol files
git clone https://github.com/randysalars/boardroom-mcp.git
cp -r boardroom-mcp/protocol-files ~/.ai/boardroom
# 2. Install the MCP server
cd boardroom-mcp && npm install && npm run build
# 3. Register as OpenClaw skill
mkdir -p ~/.openclaw/skills/boardroom
cat > ~/.openclaw/skills/boardroom/SKILL.md << 'EOF'
---
name: boardroom
description: Boardroom Mastermind Council analysis
---
EOF
# 4. Set environment variable
echo 'BOARDROOM_ROOT=~/.ai/boardroom' >> ~/.openclaw/.env
# 5. Register the skill
openclaw skills register boardroom --alwaysThe Full System
PROThe open-source MCP server is the engine. The full Boardroom system is the engine plus 2 years of hand-calibrated intelligence.