Student Founder Governor MCP Server
Provides governance layer for Notion, enforcing capacity limits, validating work plans, and logging decisions before modifying Notion data.
Click on "Install 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., "@Student Founder Governor MCP ServerWhat's my current capacity?"
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.
Student Founder Governor MCP Server
A Model Context Protocol (MCP) server designed to help student founders manage their time capacity, validate work plans, and track decision-making patterns. This server provides tools for capacity planning, constraint validation, historical analysis, and decision logging.
Why a Custom MCP Server?
While Notion AI can generate plans and suggest tasks, it cannot:
Enforce hard constraints before writing to Notion
Learn from historical execution failures
Block actions that violate capacity limits
Require explicit tradeoffs when overloaded
Maintain a long-term decision audit trail
This MCP server acts as a governance layer, not a suggestion engine. It allows AI clients like Claude to reason before modifying Notion data, ensuring plans remain realistic and sustainable.
Related MCP server: NORNR MCP Control
Demo Flow
This server is designed to support a live demo where:
AI checks remaining capacity
User attempts to add excessive work
The system blocks the action
Tradeoffs are negotiated
Decisions are logged for learning
See the Notion + Claude demo walkthrough for the full experience.
Features
Capacity Management
Track weekly time capacity and utilization
Monitor planned vs. available hours
Real-time status indicators (safe, strained, critical)
Plan Validation
Validate plans against hard time constraints
Enforce daily deep work limits
Prevent overcommitment with pre-flight checks
Historical Analytics
Track 4-week completion rates
Monitor task overrun patterns
Identify slip patterns by weekday
Surface risk flags automatically
Decision Logging
Record planning decisions and overrides
Track predicted risks
Build an audit trail for future analysis
Installation
npm installBuild
npm run build
# or
npx tscUsage
This MCP server is designed to be used with MCP-compatible clients like Claude Desktop or other AI assistants that support the Model Context Protocol.
Configuration
Add this server to your MCP client configuration:
{
"mcpServers": {
"student-founder-governor": {
"command": "node",
"args": ["/path/to/mcp-server/dist/index.js"]
}
}
}State Management
The server maintains a sample state in dist/store/state.json with the following structure:
{
"capacity": {
"week": "2024-W51",
"maxHours": 40,
"plannedHours": 0,
"deepWorkCapPerDay": 4
},
"history": {
"completionRate4w": 0.75,
"avgOverrunRatio": 1.2,
"slipByWeekday": {
"Monday": 0.5,
"Tuesday": 0.3
}
},
"decisions": []
}Note: This file-based state store is used for demonstration purposes. In a production setup, this could be replaced with Notion-backed storage or an external database.
Available Tools
get_capacity_status
Returns current capacity metrics and utilization status.
Input: None
Output:
{
"week": "2024-W51",
"max_hours": 40,
"planned_hours": 28,
"remaining_hours": 12,
"utilization_ratio": 0.7,
"status": "strained"
}Status Levels:
safe: < 70% utilizationstrained: 70-85% utilizationcritical: > 85% utilization
validate_plan
Validates a proposed plan against hard constraints.
Input:
{
"planned_tasks": [
{
"id": "task-1",
"hours": 5,
"day": "Monday",
"type": "deep"
},
{
"id": "task-2",
"hours": 3,
"day": "Tuesday",
"type": "shallow"
}
]
}Output (Success):
{
"ok": true
}Output (Violations):
{
"ok": false,
"violations": [
{
"type": "HARD_CAPACITY",
"message": "Plan exceeds remaining capacity by 5 hours"
},
{
"type": "DAILY_DEEP_WORK",
"message": "Deep work exceeds daily cap on Monday"
}
]
}Task Types:
deep: Deep work requiring focused attentionshallow: Shallow work (admin, email, meetings)
get_historical_summary
Returns historical execution patterns and risk analysis.
Input: None
Output:
{
"completion_rate_4w": 0.75,
"avg_overrun_ratio": 1.2,
"slip_by_weekday": {
"Monday": 0.5,
"Tuesday": 0.3,
"Wednesday": 0.1
},
"risk_flags": [
"LOW_COMPLETION_RATE",
"CONSISTENT_UNDERESTIMATION"
]
}Risk Flags:
LOW_COMPLETION_RATE: Completion rate < 70%CONSISTENT_UNDERESTIMATION: Average overrun ratio > 1.3
log_decision
Logs a planning or override decision for future analysis.
Input:
{
"decision_type": "OVERRIDE_CAPACITY",
"reason": "Critical deadline for investor meeting",
"predicted_risk": "HIGH"
}Output:
{
"ok": true
}The decision is logged with a unique ID and timestamp for future reference.
Use Cases
1. Weekly Planning
AI: Let me check your capacity first...
→ get_capacity_status()
AI: You have 12 hours remaining. Let's validate this plan...
→ validate_plan({ planned_tasks: [...] })
AI: Plan looks good! Logging this decision...
→ log_decision({ decision_type: "WEEKLY_PLAN", reason: "..." })2. Emergency Override
AI: I see you want to add a 10-hour task, but you only have 5 hours left.
→ validate_plan() → violations detected
User: I need to do this anyway, it's critical.
AI: Understood. Logging this override with high risk...
→ log_decision({
decision_type: "OVERRIDE_CAPACITY",
reason: "Critical investor deadline",
predicted_risk: "HIGH"
})3. Historical Analysis
AI: Let me review your execution patterns...
→ get_historical_summary()
AI: I notice you have a 75% completion rate and tend to slip on Mondays.
This suggests you might be overestimating Monday capacity.Development
Project Structure
mcp-server/
├── src/
│ ├── index.ts # Main MCP server setup
│ ├── store/
│ │ ├── state.ts # Type definitions
│ │ └── persistence.ts # State load/save
│ └── tools/
│ ├── capacity.ts # Capacity status tool
│ ├── validation.ts # Plan validation tool
│ ├── history.ts # Historical analysis tool
│ └── decisions.ts # Decision logging tool
├── dist/ # Compiled JavaScript
├── package.json
└── tsconfig.jsonTech Stack
Runtime: Node.js
Language: TypeScript
MCP SDK: @modelcontextprotocol/sdk v1.25.1
Validation: Zod v4.2.1
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Maintenance
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