Plug into curated product intelligence through MCP.

ProductManagerHub gives your team grounded answers from real product frameworks, decision criteria, and failure patterns - not generic takes. Connect once via MCP and use it inside your workflow.

Connect to our MCP

Generic Chat

“Try using RICE for prioritization. RICE stands for Reach, Impact, Confidence, and Effort...”

ProductManagerHub via MCP

“Your last 2 roadmap bets missed due to low confidence evidence. Use this 3-step decision criteria sequence from your curated knowledge base and apply the red-flag checks before committing.”

Generic Chat

“Stakeholder alignment can be improved with better communication and regular updates.”

ProductManagerHub via MCP

“For this launch, use the alignment playbook from your enterprise AI rollout case study: exec brief in week 1, risk ledger in week 2, and decision checkpoint before engineering lock.”

Our vision

We envision ProductManagerHub as the trusted intelligence layer behind every product decision: your team asks questions in their favorite AI tools, and gets grounded guidance from curated frameworks, real failure patterns, and battle-tested criteria. Over time, this becomes a living strategic memory for your product org - faster decisions, better alignment, and fewer expensive misses.

Knowledge Base Overview

45 items

Total Items

Frameworks

7 free / 4 pro

Red Flags

Decision Criteria

Framework Categories

Strategic Decisions

AI Readiness Assessment, Build vs Buy Analysis, Portfolio Optimization

AI Product Strategies

AI Feature Sequencing, AI Moat and Data Weaponization Strategy

Feature Prioritization

Infrastructure as First, Cross Roadmap Item, RICE Prioritization

Executive Communication

AI Discovery Pitch Framework, Executive AI Briefing

Operational Excellence

Technical Debt Triage and Paydown

Red Flags By Severity

Blocker4

Discovery risk, data quality gaps, execution bottlenecks, and rollout readiness concerns.

High Risk14

Discovery risk, data quality gaps, execution bottlenecks, and rollout readiness concerns.

Medium7

Discovery risk, data quality gaps, execution bottlenecks, and rollout readiness concerns.

Plug ProductManagerHub into your AI tools in minutes

This is the fun part: your AI client talks to our MCP client locally, which securely calls your ProductManagerHub MCP endpoints. Copy, paste, and you’re live.

Get an API key

Questions? Email us

Step 1

Get your API key

Create an account, then grab your key in the dashboard.

Step 2

Paste this Claude Desktop config

Replace YOUR_API_KEY and (for local dev) the URL.

Local dev

{
  "mcpServers": {
    "productmanagerhub": {
      "command": "node",
      "args": ["C:\\path\\to\\producthub\\mcp-client\\dist\\index.js"],
      "env": {
        "PMHUB_API_KEY": "YOUR_API_KEY",
        "PMHUB_API_URL": "http://localhost:3000/api/mcp"
      }
    }
  }
}

Production (npx)

{
  "mcpServers": {
    "productmanagerhub": {
      "command": "npx",
      "args": ["-y", "@productmanagerhub/mcp-client"],
      "env": {
        "PMHUB_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Step 3

Verify it works (copy/paste)

Run these against your MCP endpoints. Replace YOUR_API_KEY.

# List tools
Invoke-RestMethod -Uri "http://localhost:3000/api/mcp/tools" -Headers @{"x-api-key"="YOUR_API_KEY"} | ConvertTo-Json -Depth 5

# Execute a tool
$body = @{
  name="ai_readiness_assessment"
  arguments=@{
    product_description="B2B SaaS with AI search"
    team_size=8
    ai_experience="limited"
  }
} | ConvertTo-Json -Depth 3

Invoke-RestMethod -Uri "http://localhost:3000/api/mcp/tools" -Method POST -Headers @{"x-api-key"="YOUR_API_KEY"; "Content-Type"="application/json"} -Body $body | ConvertTo-Json -Depth 5

# List resources
Invoke-RestMethod -Uri "http://localhost:3000/api/mcp/resources" -Headers @{"x-api-key"="YOUR_API_KEY"} | ConvertTo-Json -Depth 5