# Danafitkowski Cpp Cpm Engine MCP server

Source: https://glimind.com/server/mcp-registry%2Fio.github.danafitkowski%2Fcpp-cpm-engine
Registry id: `mcp-registry/io.github.danafitkowski/cpp-cpm-engine`
Status: live (checked 2026-10-26T20:34:38.442Z)

## Measurements (30 days)

- Uptime: 99.81%
- Checks: 4919
- Outages (90 days): 14

## Install

```json
{
  "mcpServers": {
    "danafitkowski-cpp-cpm-engine-mcp-server": {
      "type": "http",
      "url": "https://mcp.criticalpathpartners.ca/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http danafitkowski-cpp-cpm-engine-mcp-server https://mcp.criticalpathpartners.ca/mcp
```

## Tools (13)

- `claim_workbench_evidence_ledger`: Forensic claim workbench — analyzes a folder of mixed evidence (XER chain + MSG/PDF/DOCX/XLSX correspondence) and produces a unified workbench dashboard. Built 
- `collapsed_as_built`: Collapsed As-Built / But-For analysis on a post-impact XER. Implements AACE RP 29R-03 §3.8 Modeled / Subtractive / Single Base method (paired with MIP 3.3 Windo
- `concurrent_delay_matrix`: Build the per-window x per-party concurrent-delay attribution matrix from a chronological list of XER snapshots. Implements the per-window concurrency view per 
- `critical_path_validator`: Critical-path validation, logic health, and DCMA-14 assessment of a Primavera P6 schedule. Runs the CPP critical-path validator: checks for false criticality, c
- `dcma14_health_check`: Full Schedule Health Dashboard HTML report — DCMA-14 + CPLI + BEI + variance/slip register against the baseline. Wraps the CPP Schedule Health Review skill, whi
- `forensic_windows_analysis`: Run forensic windows analysis (AACE RP 29R-03 §3.3, MIP 3.3 Observational / Dynamic / Contemporaneous As-Is) across multiple Primavera P6 XER snapshots and retu
- `monte_carlo_p50_p80`: Monte Carlo Schedule Risk Analysis — P10/P50/P80/P90 completion-date forecast for a Primavera P6 schedule. Implements an AACE-style quantitative SRA (the same m
- `path_explorer`: Logic-trace driver-chain explorer — answers "WHY is this activity critical?" and "WHAT does it drive?". Traces driving predecessors backward from a target activ
- `qramm_maturity`: QRAMM-aligned maturity reading for an SRA result. Places a Schedule Risk Analysis run (from ``monte_carlo_p50_p80`` or any equivalent dict) on the five named ma
- `slip_velocity`: Per-window slip velocity & acceleration trend across XER snapshots. Computes three signed metrics per window from the underlying forensic windows analysis: - sl
- `time_impact_analysis_fragnet`: Time Impact Analysis (TIA) — prospective fragnet insertion into a pre-impact baseline schedule. Supports two modes. **Single-base mode** (legacy): supply ``base
- `woet_classifier`: Worked-vs-On-time Execution Timeline (WOET) per-activity day-by-day classification of as-built execution against baseline. For each pairable activity (matched b
- `xer_parser`: Parse a Primavera P6 XER file and return a TABLE SUMMARY (not the full row-level data — XER row dumps explode the MCP context window). For each table in the XER

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.