pm-data
Parse and convert project data from 8 formats (MSPDI, P6 XER, NISTA, Jira, Monday, etc.)
MCP 服务配置
复制以下 JSON 到 OPClaw 或其他 MCP 客户端的配置文件中即可使用
{
"mcpServers": {
"pm-mcp-servers": {
"args": [
"pm-mcp-servers@0.3.0"
],
"command": "uvx"
}
}
}
可用工具 (5 个)
该服务在 MCP 协议中暴露的工具,AI 可按需调用
tavily_search 14 个参数 需填 1 项
Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.
必填参数:query
tavily_extract 6 个参数 需填 1 项
Extract content from URLs. Returns raw page content in markdown or text format.
必填参数:urls
tavily_crawl 11 个参数 需填 1 项
Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.
必填参数:url
tavily_map 8 个参数 需填 1 项
Map a website's structure. Returns a list of URLs found starting from the base URL.
必填参数:url
tavily_research 2 个参数 需填 1 项
Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.
必填参数:input
服务介绍
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This repository is no longer maintained or supported.
- The contact email info@pdataskforce.com is no longer active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
Built to support the NISTA trial and improve UK project delivery.