
Critical Path Partners forensic scheduling MCP
@danafitkowski
About Critical Path Partners forensic scheduling MCP
13 tools for Primavera P6 forensic delay analysis — AACE windows (29R-03 MIP 3.3), DCMA-14 health checks, Monte Carlo SRA with AACE 122R-22 QRAMM maturity, TIA fragnet (MIP 3.7), collapsed as-built (MIP 3.8), and claim workbench evidence ledger. Open-source CPM engine (MIT) at gi
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"criticalpathpartners": {
"url": "https://mcp.criticalpathpartners.ca/mcp",
"transport": "streamableHttp"
}
}
}Tools
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Overview
What is Critical Path Partners forensic scheduling MCP?
A forensically-defensible CPM engine that is AACE-canonical, Daubert-disclosed, and bit-identical between JavaScript and Python. It is maintained by Critical Path Partners for forensic scheduling experts, academics, and contractors requiring a Daubert-compliant foundation for critical-path analysis.
How to use Critical Path Partners forensic scheduling MCP?
Install via npm install @critical-path-partners/cpm-engine, then call computeCPM() with an array of activities, relationships, and options (e.g., data date, calendar map). The result includes project finish date, critical path, and a manifest with method labels and topology hash.
Key features of Critical Path Partners forensic scheduling MCP
- Open source (MIT licensed)
- AACE-canonical method labels (29R-03, 49R-06, 52R-06)
- Built-in Daubert disclosure (FRCP 26(a)(2)(B))
- JavaScript–Python bit-identical parity (cross-validated)
- Topology fingerprint hash (SHA-256) for copy-detection
- 66 multi-jurisdiction holiday calendars
Use cases of Critical Path Partners forensic scheduling MCP
- Forensic delay analysis (windows, collapsed as-built, prospective TIA)
- Claim packages and EOT bundles with exhibits
- Daubert disclosures and FRCP 26(a)(2)(B) reports
- Schedule risk analysis (Monte Carlo, Bayesian updates)
- Schedule health checks (DCMA-14, A-F grading)
FAQ from Critical Path Partners forensic scheduling MCP
What makes the engine Daubert-compliant?
Every computation emits a manifest identifying methods by AACE‑canonical labels (e.g., MIP 3.3), and a separate Daubert disclosure document (DAUBERT.md) is provided as a starting point for expert reports.
What runtime does the server require?
The engine is available as an npm package for Node.js and has a bit-identical Python sibling; both produce the same numerical results.
Where does my schedule data live?
All computation is performed locally. No activity data or results are sent to any external server.
Does the engine support multi-jurisdiction holidays?
Yes, it includes holiday calendars for 66 jurisdictions (US Federal + 50 states + DC, Canada Federal + 13 provinces).
How do I verify that two schedules are identical?
Use computeTopologyHash() to obtain a SHA-256 hash over canonical inputs; identical hashes indicate identical schedules regardless of UID rotation.
Frequently asked questions
What makes the engine Daubert-compliant?
Every computation emits a manifest identifying methods by AACE‑canonical labels (e.g., MIP 3.3), and a separate Daubert disclosure document (`DAUBERT.md`) is provided as a starting point for expert reports.
What runtime does the server require?
The engine is available as an npm package for Node.js and has a bit-identical Python sibling; both produce the same numerical results.
Where does my schedule data live?
All computation is performed locally. No activity data or results are sent to any external server.
Does the engine support multi-jurisdiction holidays?
Yes, it includes holiday calendars for 66 jurisdictions (US Federal + 50 states + DC, Canada Federal + 13 provinces).
How do I verify that two schedules are identical?
Use `computeTopologyHash()` to obtain a SHA-256 hash over canonical inputs; identical hashes indicate identical schedules regardless of UID rotation.
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