pAIchart — AI-Native Delivery Management + MCP Hub

pAIchart is an MCP hub for AI-native delivery management — POVs, tasks, and phases you drive in natural language — plus a registry of external MCP services you can discover, call, and orchestrate into multi-service workflows.

Anyone can self-register a service; agents and AI clients then reach all of them through a single Hub with trust-level authentication and per-user OAuth passthrough.

What pAIchart Does

Delivery management (the core)

• POVs → Phases → Tasks — run proof-of-value engagements as structured, AI-readable delivery plans

• Natural-language operation — ask "Which of my POVs are at risk?" or "show open tasks for BlackEye" — no UI required

• AI agents on your work — configure, assign, and execute agents against delivery tasks

• Portfolio analytics — health, insights, and execution metrics across your POVs

MCP service hub

• Free Service Registration — Comprehensive guides available via "/prompt list" or as MCP resources

• Service Discovery — AI agents find services by capability, not by name

• Multi-Service Workflows — Chain services sequentially, in parallel, or conditionally with variable passing

• Per-User Authentication — Each user's operations run as themselves via External OAuth (validated with Snowflake)

• Trust Level System — 6-tier security model controls token forwarding (INTERNAL → TRUSTED → OWNER → TEAM_MEMBER → SCOPED → ANONYMOUS)

• JWKS Token Validation — RS256 asymmetric cryptography, public-key verification, no shared secrets

• Per-Service Audience Scoping — Hub-minted access tokens carry a per-service audience (RFC 8707 resource indicators): each service receives a short-lived credential scoped to only itself, so a token leaked from one service can't be replayed against another. Services that validate it via JWKS can accept pAIchart-issued identity instead of static API keys in URLs.

• Trustworthy Error-Recovery Signals — When a service call fails, the Hub returns facts an AI client can act on — the honoured timeout, the service's recent success rate, and recovery guidance that never points at a blind health check — rather than unvalidated verdicts that can mislead. Built so the client recovers on its own; see the Error Recovery Signals case study.

Related MCP server: MCP-NG

Get Started

pAIchart is a hosted MCP hub — nothing to install. Point your AI client at the endpoint, authenticate, and start asking in natural language.

• Hub access: https://paichart.app/mcp

• Connect with: Claude Desktop (GitHub OAuth) or ChatGPT (Microsoft OAuth)

• First thing to say: "Help me get started with paichart" — or run /prompt list to see every guided workflow

• Privacy: PRIVACY-DEMO.md — what a demo account holds, what it can do, 30-day auto-deletion

Once you're connected, try:

• "Which of my POVs are at risk?" — delivery analytics, answered directly

• "Discover services" — browse the registry by capability

• "Run the prompt energy_operations_optimizer" — correlates weather forecasts with energy data into operational recommendations, a multi-service workflow across two live services

Under the Hood

Every request is either answered directly or composed into a workflow across services — and every external call runs as you, never as a shared platform account:

You (Claude Desktop / ChatGPT)
 → authenticate to the pAIchart Hub
 → ask in natural language, e.g.
 • "Which of my POVs are at risk?" → project / analytics tools answer directly
 • "Texas energy mix + this week's weather" → Hub composes a multi-service workflow
 → for external service calls:
 → Hub discovers services by capability, determines trust level, mints a per-service JWT
 → the external service validates it via JWKS — no shared API keys
 → operations execute as the authenticated user

Live Services

Register Your MCP Service

Any MCP service can register with the Hub in one command:

registry(action: "register", {
 name: "my-service",
 description: "What your service does",
 endpoint: "https://my-service.com/mcp",
 category: "data-services"
})

Services that support External OAuth (like Snowflake, Databricks) get per-user authentication automatically.

Learn

• MCP Tool Excellence — a 12-chapter tutorial series on building MCP tools AI clients can call without external documentation, extracted from pAIchart's own production audits: tutorials/README.md

Links

• Platform: paichart.app

• JWKS: https://paichart.app/api/auth/jwks

• Documentation: provided as an MCP resource (or run /prompt list) in your AI client

• Demo User Privacy: PRIVACY-DEMO.md — what a demo account holds, what it can do, 30-day auto-deletion

Keywords

mcp mcp-hub mcp-server mcp-orchestration model-context-protocol ai-native delivery-management proof-of-value pov task-management project-management ai-services service-discovery external-oauth jwks per-service-audience rfc8707 per-user-authentication workflow-orchestration error-recovery mcp-tutorials claude-desktop chatgpt snowflake context7

Maintenance

Resources

• Remote Server
• GitHub Repository
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Tools

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