Skip to main content

MCP servers for AI-enabled project management. Enables Claude to interact with PM data.

Project description

PM MCP Servers

MCP servers for AI-enabled project management. Enables Claude to interact with PM data.

Part of the PDA Platform.

Overview

PM MCP Servers provides Model Context Protocol (MCP) servers that enable Claude Desktop and other MCP clients to interact with project management data. Built to support the NISTA Programme and Project Data Standard trial.

Features

  • pm-data-server: Load, query, and manipulate PM data
  • pm-validate-server: Validate PM data against standards
  • pm-analyse-server: Analyze PM data for insights
  • pm-benchmark-server: Benchmark PM AI capabilities

Installation

pip install pm-mcp-servers

Quick Start

Configure Claude Desktop

Add to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "pm-data": {
      "command": "pm-data-server",
      "args": []
    }
  }
}

Example Queries

Once configured, you can ask Claude:

  • "Load /projects/building.mpp and show the critical path"
  • "What tasks are at risk of slipping?"
  • "Convert this project to NISTA format"
  • "Validate this project against NISTA requirements"

Available Servers

pm-data-server

Core server for PM data interaction.

Tools:

  • load_project: Load a project file
  • query_tasks: Query tasks by criteria
  • get_critical_path: Find critical path
  • export_project: Export to different formats

pm-validate-server

Validation server for PM data quality.

Tools:

  • validate_nista: Validate NISTA compliance
  • validate_structure: Check structural integrity
  • check_dependencies: Validate task dependencies

pm-analyse-server

Analysis server for PM insights.

Tools:

  • analyze_risks: Identify project risks
  • forecast_completion: Predict completion dates
  • resource_utilization: Analyze resource usage

pm-benchmark-server

Benchmarking server for PM AI evaluation.

Tools:

  • run_benchmark: Execute benchmark tasks
  • compare_results: Compare AI performance

Development

# Clone repository
git clone https://github.com/PDA-Task-Force/pda-platform.git
cd pda-platform/packages/pm-mcp-servers

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

Acknowledgments

Developed by members of the PDA Task Force.

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

License

MIT License - see LICENSE for details.

Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pm_mcp_servers-0.2.0.tar.gz (18.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pm_mcp_servers-0.2.0-py3-none-any.whl (15.1 kB view details)

Uploaded Python 3

File details

Details for the file pm_mcp_servers-0.2.0.tar.gz.

File metadata

  • Download URL: pm_mcp_servers-0.2.0.tar.gz
  • Upload date:
  • Size: 18.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.6

File hashes

Hashes for pm_mcp_servers-0.2.0.tar.gz
Algorithm Hash digest
SHA256 33ca88b5a69003e3cc827d3660ce79217a509a465a765dd7c27f9b17d508964f
MD5 2c9842d85bb1df8b73a9a40b3fa6c258
BLAKE2b-256 8900dbe7a2ab33e0992e1de8e6f8db230c39b47a52924d59c38d170eb28efb35

See more details on using hashes here.

File details

Details for the file pm_mcp_servers-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: pm_mcp_servers-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 15.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.6

File hashes

Hashes for pm_mcp_servers-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f795870c196fa28d61f4a48a1a9ef96c9b9832a3dccbf402938c4ee2194b4b72
MD5 b6f8413b22b4bdfe75b24e80a5538c7c
BLAKE2b-256 5d3fbddb4d6c88572f09e8193da455429be8a08b0fb57775b224bf2f58ebfc90

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page