Project Management AI Analysis MCP server

Read from the package source without running it. The installed server may list more.

• assess_health

  Assess multi-dimensional project health across schedule, cost, scope, resource, and quality dimensions with weighted scoring

• compare_baseline

  Compare current project state against baseline to identify schedule, duration, and cost variances with severity classification

• convert_format

  Convert project to different format (MSPDI XML, JSON, NISTA)

• detect_outliers

  Detect anomalies in task data across duration, progress, float, and dates using statistical analysis

• forecast_completion

  Forecast project completion date using multiple methods (EVM, Monte Carlo, Reference Class, ML Ensemble) with confidence intervals

• get_critical_path

  Get critical path tasks and optionally near-critical tasks (within 5 days float)

• get_dependencies

  Get task dependencies (predecessors/successors) for dependency analysis

• get_project_summary

  Get high-level project summary (task counts, dates, critical path length, source format)

• identify_risks

  Identify project risks using AI-powered risk engine across schedule, cost, resource, scope, technical, and external dimensions

• load_project

  Load a project file from various PM tools (MS Project, P6, Jira, Monday, Asana, Smartsheet, GMPP, NISTA) and return canonical representation

• query_tasks

  Query tasks with optional filters (status, critical path, milestones, assignee, dates)

• suggest_mitigations

  Generate AI-powered mitigation strategies for identified risks with effectiveness ratings and implementation steps

• validate_customwrite action

  Run custom validation rules defined by the user. Supports multiple condition types for organization-specific requirements.

• validate_nista

  Validate against NISTA Programme and Project Data Standard. Essential for UK government project compliance. Checks required fields, DCA values, and formats per NISTA specification.

• validate_semantic

  Validate business rules and scheduling logic. Checks schedule logic, negative float, resource overallocation, constraint violations, cost consistency, baseline variance, and milestone dates.

• validate_structure

  Validate project data structure and integrity. Checks for orphan tasks, circular dependencies, invalid references, duplicate IDs, hierarchy integrity, date consistency, and assignment validity.

• Code scan16 source files scanned25/25
• –Live reliabilityno gateway calls yet and no remote to proben/a
• –Tool poisoningtools not inspected (local package is not executed); not countedn/a
• Auth qualitylocal package, no credentials required12/15
• Maintenancerepository archived0/15
• Maintainer identitynamespace and repository owner differ4/10

Project Management AI Analysis: common questions

Is Project Management AI Analysis MCP server safe?

With care: it is graded C, so read the findings first (63/100). Read the Project Management AI Analysis safety report

How do I install Project Management AI Analysis?

It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.

Does Project Management AI Analysis need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is Project Management AI Analysis maintained?

The last commit was 252 days ago (2026-02-02). The latest release is v0.3.0.

What can I use instead of Project Management AI Analysis?

Servers from other publishers that do the same job: Rsdoctor MCP server.