ahmed-khalil-hafsi/P2Predict
by Various
Parametric price benchmarking for engineering and procurement trade-offs. Agentic first, runs on your data, stays on your machine.
MCP
ahmed-khalil-hafsi/P2Predict
Added 21 Sept 2026
Overview
P2Predict is a Python tool for parametric price benchmarking, supporting engineering and procurement trade-off analysis. It is agentic first and designed to run on your own data while staying on your machine. The repository is at an early stage with limited stars.
Best for
Best for
Engineers and procurement analysts needing on-premise parametric price benchmarking
Use cases
- Benchmark parametric prices for engineering components
- Evaluate procurement trade-offs using local data
- Run agentic price analysis without cloud uploads
How to use
Install
pip install "p2predict[mcp]"Notes
P2Predict is a Python tool for parametric price benchmarking, supporting engineering and procurement trade-off analysis. It is agentic first and designed to run on your own data while staying on your machine. The repository is at an early stage with limited stars.
2 stars on GitHub. Last updated 2026-09-17.
Use cases
- Benchmark parametric prices for engineering components
- Evaluate procurement trade-offs using local data
- Run agentic price analysis without cloud uploads
Pros
- Runs locally, keeping sensitive data on your machine
- Agentic first design for automated analysis workflows
- Focused on engineering and procurement decision support
Cons
- Very early stage with only 2 stars
- Limited community and documentation evidence
- Narrow scope may not suit general pricing tasks
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Runs locally, keeping sensitive data on your machine
- Agentic first design for automated analysis workflows
- Focused on engineering and procurement decision support
Cons
- Very early stage with only 2 stars
- Limited community and documentation evidence
- Narrow scope may not suit general pricing tasks
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