pdunovits avatar

Pabs

pdunovits/pabs-mcp

Connects your AI coding tools to PABS, a product strategy platform that generates PRDs, competitor analysis, and design hypotheses from a brief. Your AI can call get_full_context to load the entire strategy at session start, then use ask_pabs_agent to check feature alignment or report_learning to push observations back into the strategy loop. Each learning gets evaluated by PABS and queued for founder review before the strategy updates. Useful when you want your AI builder to know the target audience and design constraints before writing code, and to surface drift between what was planned and what got built. Authentication is one bearer token per plan, generated from the PABS Connect tab.

tools
18
transport
HTTP
last updated
May 29, 2026

Tools

18 tools

Public tool metadata for what this MCP can expose to an agent.

get_full_contextEverything in one call: brief, strategy, competitor analysis, documents, decisions, hypotheses, action plan, latest pulse, recent learnings.

Everything in one call: brief, strategy, competitor analysis, documents, decisions, hypotheses, action plan, latest pulse, recent learnings.

No parameter schema in public metadata yet.

get_briefProblem statement, target audience, goals, constraints, timeline

Problem statement, target audience, goals, constraints, timeline

No parameter schema in public metadata yet.

get_product_strategyDesign hypotheses, customer goals, pain points, design vision, success metrics, experience principles

Design hypotheses, customer goals, pain points, design vision, success metrics, experience principles

No parameter schema in public metadata yet.

get_competitor_analysisMarket intelligence, competitive positioning, opportunity analysis

Market intelligence, competitive positioning, opportunity analysis

No parameter schema in public metadata yet.

get_prdProduct Requirements Document generated for AI code builders

Product Requirements Document generated for AI code builders

No parameter schema in public metadata yet.

get_documentsAll generated documents: PRD, Statement of Work, Venture Brief

All generated documents: PRD, Statement of Work, Venture Brief

No parameter schema in public metadata yet.

get_decisionsKey assumptions, information gaps with priority/impact, recommended next steps

Key assumptions, information gaps with priority/impact, recommended next steps

No parameter schema in public metadata yet.

get_hypothesesDesign hypotheses with target audience and success indicators

Design hypotheses with target audience and success indicators

No parameter schema in public metadata yet.

get_action_planStaged activities with tools, durations, and deliverables

Staged activities with tools, durations, and deliverables

No parameter schema in public metadata yet.

get_pulseCurrent strategic Pulse: verdict, recommended next move, activation level

Current strategic Pulse: verdict, recommended next move, activation level

No parameter schema in public metadata yet.

get_learningsAll captured learnings — evaluated and decided — with the full decision history

All captured learnings — evaluated and decided — with the full decision history

No parameter schema in public metadata yet.

get_pending_learningsLearnings PABS has evaluated but that need a human decision

Learnings PABS has evaluated but that need a human decision

No parameter schema in public metadata yet.

get_pulse_scheduleCurrent Pulse cadence: day, time, timezone, frequency, next run

Current Pulse cadence: day, time, timezone, frequency, next run

No parameter schema in public metadata yet.

ask_pabs_agentAsk a strategic question. Returns alignment score, recommendations, and considerations. Automatically captures observations or implementation drift.

Ask a strategic question. Returns alignment score, recommendations, and considerations. Automatically captures observations or implementation drift.

No parameter schema in public metadata yet.

report_learningPush a real-world observation into the strategy feedback loop. PABS evaluates its impact and queues it for the founder to review.

Push a real-world observation into the strategy feedback loop. PABS evaluates its impact and queues it for the founder to review.

No parameter schema in public metadata yet.

decide_learningApprove, reject, or modify a pending learning inline — without opening PABS.

Approve, reject, or modify a pending learning inline — without opening PABS.

No parameter schema in public metadata yet.

trigger_pulseQueue a fresh strategic Pulse after a significant build session or analytics review.

Queue a fresh strategic Pulse after a significant build session or analytics review.

No parameter schema in public metadata yet.

schedule_pulseSet the agentic Pulse cadence (frequency, day, hour, timezone).

Set the agentic Pulse cadence (frequency, day, hour, timezone).

No parameter schema in public metadata yet.

Sponsors

Readme

PABS MCP Server

Give your AI coding tools live access to your product strategy.

PABS is a product strategy platform that turns a brief into a full strategy — hypotheses, competitor analysis, PRD, and a living pulse of your venture's health. The MCP server exposes that strategy to any MCP-compatible AI tool so it can build with context, not guesses.

When your AI builder knows the target audience, design hypotheses, and current strategic verdict, it makes better decisions. When it spots a gap between what was planned and what was built, it can report it back — and PABS queues it for your review.


Connection

Transport: Streamable HTTP (MCP 2025 spec) Server URL: https://pabs.co.nz/api/mcp/{your-token} Authentication: Bearer token (one per plan, generated in the PABS app)

Get your token

  1. Open your plan in PABS
  2. Go to the Connect tab (or click the plug icon)
  3. Click Generate Token
  4. Copy the server URL — it includes your token

Connect to your AI tool

Claude Desktop

Add to claude_desktop_config.json:


View the full README on GitHub

Details

Repository
github.com/pdunovits/pabs-mcp
Website
pabs.co.nz
Transport
HTTP
Registry
MCP registry, active