PDA Platform

NOTICE: The PDA Task Force closed on 30 January 2026 This repository is no longer maintained or supported. - The contact email info@pdataskforce.com is no longer active - For questions, contact the final Chair: Donnie MacNicol at donnie@teamanimation.co.uk - A maintained fork is available at: https://github.com/antnewman/pda-platform

Open-source infrastructure for AI-enabled project delivery.

  

Overview

The PDA Platform provides the data infrastructure needed for AI to improve project delivery. Built to support the NISTA Programme and Project Data Standard trial.

This work was made possible by:

• The PDA Task Force White Paper identifying AI implementation barriers in UK project delivery
• The NISTA Programme and Project Data Standard and its 12-month trial period

The Problem

UK major infrastructure projects have a success rate of approximately 0.5%. The Government Major Projects Portfolio shows 84% of projects rated Amber or Red. AI has potential to help, but lacks standardised data infrastructure.

The Solution

| Component | Description | Status | |-----------|-------------|--------| | pm-data-tools | Universal PM data parser (8 formats + NISTA) | v0.2.0 ✅ | | agent-task-planning | AI reliability framework | v1.0.0 ✅ | | pm-mcp-servers | MCP servers for Claude integration | Phase 1 ✅ | | Specifications | Canonical model, benchmarks, synthetic data | Published ✅ |

Quick Start

# Install the core library
pip install pm-data-tools

# Parse any PM file
from pm_data_tools import parse_project
project = parse_project("schedule.mpp")

# Validate NISTA compliance
from pm_data_tools.validators import NISTAValidator
result = NISTAValidator().validate(project)
print(f"Compliance: {result.compliance_score}%")

Packages

pm-data-tools

Universal parser and validator for project management data.

• Formats: MS Project, Primavera P6, Jira, Monday, Asana, Smartsheet, GMPP, NISTA
• Features: Parse, validate, convert, migrate
• Install: pip install pm-data-tools

agent-task-planning

AI reliability framework with confidence extraction and outlier mining.

• Features: Multi-sample consensus, diverse alternative generation
• Install: pip install agent-task-planning

pm-mcp-servers

MCP servers enabling Claude to interact with PM data.

• Servers: pm-data, pm-validate, pm-analyse, pm-benchmark
• Install: pip install pm-mcp-servers

Specifications

All specifications are in the specs/ directory:

| Spec | Description | |------|-------------| | Canonical Model | 12-entity JSON Schema for PM data | | MCP Servers | 4 servers, 19 tools for AI integration | | Benchmarks | 5 evaluation tasks for PM AI | | Synthetic Data | Privacy-preserving data generation |

Repository Structure

pda-platform/
├── specs/           # Technical specifications
├── packages/        # Python packages (each publishable to PyPI)
│   ├── pm-data-tools/
│   ├── agent-task-planning/
│   └── pm-mcp-servers/
├── docs/            # Documentation
└── examples/        # Usage examples

License

MIT License - see LICENSE

Authors

Members of the PDA Task Force

Acknowledgments

• PDA Task Force White Paper on AI implementation barriers
• NISTA Programme and Project Data Standard
• The open-source community

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Built to support the NISTA trial and improve UK project delivery.