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Critical Path Partners
io.github.danafitkowski/cpp-cpm-engine · v2.10.12
New (7 days)
Measured by MCP Station
| Last check | Reachable |
|---|---|
| Checked at | — |
| Check success 7 / 30 days | — |
| First-try success 30 days | — |
| Median response | — |
| Lookups 30 days | — |
| Authentication | No auth |
| MCP version | 2025-06-18 |
| Rank score | — |
| Declared risk | Not declared (tools carry no read/destructive hints) |
| Capabilities declared | experimental, prompts, resources, tools |
| Tool definitions | 13 tools · with description 100% · input schema is an object 100% · read/destructive hints 0% |
Description written by the publisher, not verified
Forensic scheduling MCP for Primavera P6 (XER): AACE windows, DCMA-14, Monte Carlo, TIA.
Connect
streamable-http · https://mcp.criticalpathpartners.ca/mcp
claude mcp add --transport http cpp-cpm-engine https://mcp.criticalpathpartners.ca/mcp{
"mcpServers": {
"cpp-cpm-engine": {
"url": "https://mcp.criticalpathpartners.ca/mcp"
}
}
}Tools as reported by the server
forensic_windows_analysisRun forensic windows analysis (AACE RP 29R-03 §3.3, MIP 3.3 Observational / Dynamic / Contemporaneous As-Is) across multiple Primavera P6 XER snapshots and return the full analysis dict. This is the headline forensic tool — it computes per-window completion shifts, per-window slip registers (per-actconcurrent_delay_matrixBuild the per-window x per-party concurrent-delay attribution matrix from a chronological list of XER snapshots. Implements the per-window concurrency view per AACE RP 29R-03 §3.3.I (apportionment) and §4.2 (concurrency). Where ``forensic_windows_analysis`` answers "how many days does each party ownwoet_classifierWorked-vs-On-time Execution Timeline (WOET) per-activity day-by-day classification of as-built execution against baseline. For each pairable activity (matched by ``task_code``), classifies execution into 4 day-states: - PROGRESS: work performed during the baseline-planned window - GAIN: work performslip_velocityPer-window slip velocity & acceleration trend across XER snapshots. Computes three signed metrics per window from the underlying forensic windows analysis: - slip_velocity_days_per_day: completion shift / window duration (positive = slipping, negative = recovering). Numerator is the WORKING-day compcollapsed_as_builtCollapsed 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 Windows for the dual-method gap report per SCL §11.5). Validates a forensic windows analysis (MIP 3.3) by independently computing the same projectime_impact_analysis_fragnetTime Impact Analysis (TIA) — prospective fragnet insertion into a pre-impact baseline schedule. Supports two modes. **Single-base mode** (legacy): supply ``baseline_xer_path`` or ``baseline_xer_content``. All fragnets are inserted into the same shared baseline XER and impact is measured against thatcritical_path_validatorCritical-path validation, logic health, and DCMA-14 assessment of a Primavera P6 schedule. Runs the CPP critical-path validator: checks for false criticality, constraint-driven CP segments, open ends, broken logic, and surfaces a DCMA-14 block with the 14 metrics (logic, leads, lags, FS%, hard constdcma14_health_checkFull Schedule Health Dashboard HTML report — DCMA-14 + CPLI + BEI + variance/slip register against the baseline. Wraps the CPP Schedule Health Review skill, which produces a self-contained ~1.3 MB HTML dashboard. The dashboard renders DCMA metrics, charts, baseline-vs-current variance, slip registerpath_explorerLogic-trace driver-chain explorer — answers "WHY is this activity critical?" and "WHAT does it drive?". Traces driving predecessors backward from a target activity to project start (the "why critical" chain) and/or driving successors forward to project finish (the "what it drives" chain). Detects comonte_carlo_p50_p80Monte Carlo Schedule Risk Analysis — P10/P50/P80/P90 completion-date forecast for a Primavera P6 schedule. Implements an AACE-style quantitative SRA (the same math as CPP's browser Tool_11 Portfolio Risk Engine, scripted Python counterpart). For each iteration, every activity duration is sampled froqramm_maturityQRAMM-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 maturity levels of AACE RP 122R-22 (Quantitative Risk Analysis Maturity Model), section 3: level 1 Reactive, level 2 Ad-hoc, level 3 Centralizclaim_workbench_evidence_ledgerForensic claim workbench — analyzes a folder of mixed evidence (XER chain + MSG/PDF/DOCX/XLSX correspondence) and produces a unified workbench dashboard. Built from the real-world workflow where forensic delay analysis starts from a folder containing schedule updates, owner correspondence, RFIs, chaxer_parserParse 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, returns the table name, field list, and record count. Per-row data is intentionally omitted — for forensic / DCMA / windows analysis use t
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