Project Management AI Analysis

io.github.antnewmanPublished by GitHub account antnewmanv0.3.0Updated Oct 24, 2026

AI-powered project analysis with risk identification, forecasting, and mitigation generation

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Overview

AI-generated overview

Part of the pm-mcp-servers suite, it gives an AI assistant tools for project analysis: risk identification, forecasting and mitigation generation.

What you can do
  • Analyse project management data for risks and produce mitigation suggestions
  • Forecast project outcomes from parsed PM data
  • Work alongside sibling servers in the same package for parsing, validation and benchmarking of PM data
  • Support AI-assisted project delivery on data following the NISTA programme and project data standard
When to use it
Worth adding when you want an assistant to review project schedules or plans for risk and produce forecasts and mitigation ideas, especially in UK public-sector or infrastructure project delivery contexts.
Requirements
Runs as a local stdio process installed from the PyPI package pm-mcp-servers (Python). No authentication, environment variables or headers are declared. Desktop-only; not available as a web executable.
Before you install
The README states the underlying PDA Task Force repository is no longer maintained or supported and its contact email is inactive, with a maintained fork named separately; check you are installing the maintained version. Project data you pass in is handled by the local process.

Installation

In SourceWeft

  1. Open Project Management AI Analysis in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

PDA Platform

NOTICE: The PDA Task Force closed on 30 January 2026

This repository is no longer maintained or supported.

Open-source infrastructure for AI-enabled project delivery.

[License: MIT] [DOI] [PyPI - pm-data-tools]

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

ComponentDescriptionStatus
pm-data-toolsUniversal PM data parser (8 formats + NISTA)v0.2.0 ✅
agent-task-planningAI reliability frameworkv1.0.0 ✅
pm-mcp-serversMCP servers for Claude integrationPhase 1 ✅
SpecificationsCanonical model, benchmarks, synthetic dataPublished ✅

Quick Start

bash
# Install the core librarypip install pm-data-tools
# Parse any PM filefrom pm_data_tools import parse_projectproject = parse_project("schedule.mpp")
# Validate NISTA compliancefrom pm_data_tools.validators import NISTAValidatorresult = 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:

SpecDescription
Canonical Model12-entity JSON Schema for PM data
MCP Servers4 servers, 19 tools for AI integration
Benchmarks5 evaluation tasks for PM AI
Synthetic DataPrivacy-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

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

Source: README.md at commit f73b088

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.3.0LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts