ConstructAI

AI-powered construction project control assistant combining Civil Engineering project controls, Model Context Protocol (MCP), SQLAlchemy, and a local LLM.

🚧 Overview

ConstructAI is an AI assistant designed for construction project control.

It allows users to ask project-control questions in natural language and uses MCP tools to retrieve project data, analyze schedules, identify risks, evaluate delays, and recommend recovery actions.

Key Capabilities

• Analyze project schedule status
• Identify critical activities
• Find activities by name
• Analyze construction delays
• Determine delay impact on project completion
• Identify delayed activities
• Analyze activity dependencies
• Identify resource bottlenecks
• Analyze project risks
• Generate schedule recovery strategies
• Provide project-control summaries

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🏗️ Architecture

User
  │
  ▼
Natural Language Query
  │
  ▼
Qwen3 8B (Local via Ollama)
  │
  ▼
MCP Tool Calling
  │
  ▼
ConstructAI MCP Server
  │
  ├── Schedule & CPM
  ├── Delay Analysis
  ├── Risk Analysis
  ├── Resource Analysis
  └── Schedule Recovery
  │
  ▼
SQLAlchemy
  │
  ▼
Project Database
  │
  ▼
Engineering Analysis
  │
  ▼
AI Recommendation

---

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🎬 Demo

AI + MCP Tool Execution

ConstructAI accepts a natural-language construction project-control question and automatically selects the required MCP tools.

Delay Impact & Schedule Recovery

For a delayed activity, ConstructAI identifies the activity, calculates the impact on project completion, identifies affected activities, and recommends recovery actions.

🤖 Technology Stack

• Python
• MCP 2.1.1
• Qwen3 8B
• Ollama
• SQLAlchemy
• SQLite
• Natural-language tool calling

The LLM runs locally through Ollama, so the current system does not require a paid AI API.

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🔧 MCP Tools

ConstructAI currently provides 11 MCP tools:

#	Tool	Purpose
1	analyze_delay	Analyze the impact of an activity delay
2	project_status	Retrieve overall project status
3	critical_activities	Identify critical activities
4	activity_details	Retrieve detailed activity information
5	delayed_activities	Identify delayed activities
6	activity_dependencies	Analyze predecessor and successor relationships
7	schedule_recovery	Generate schedule recovery options
8	resource_bottleneck	Identify resource bottlenecks
9	project_risk_analysis	Analyze project risks
10	project_control_summary	Provide an overall project-control summary
11	find_activity_tool	Find activities by name

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📊 Project Control Capabilities

Schedule Management

ConstructAI can analyze:

• Planned start and finish dates
• Activity durations
• Early and late dates
• Total float
• Critical activities
• Activity dependencies
• Project completion dates

Delay Analysis

The system can determine:

• Delayed activity
• Delay duration
• Original project finish
• New project finish
• Project completion impact
• Affected downstream activities
• Delay priority
• Recommended corrective action

Schedule Recovery

ConstructAI can recommend strategies such as:

• Expediting material procurement
• Increasing manpower
• Increasing working hours
• Prioritizing critical activities
• Coordinating successor activities
• Controlled activity overlap

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🧠 Example AI Workflow

User Question

Electrical Rough-in is delayed by 3 days because of a material shortage. What is the impact on Project 3 and how can we recover the schedule?

Tool Execution

User Question
     │
     ▼
find_activity_tool
     │
     ▼
Find Electrical Rough-in → Activity ID = 33
     │
     ▼
analyze_delay
     │
     ▼
Calculate Delay Impact
     │
     ▼
schedule_recovery
     │
     ▼
Generate Recovery Strategy
     │
     ▼
Engineering Recommendation

Result

Original Project Finish : 2026-11-06
New Project Finish      : 2026-11-09
Project Impact          : 3 days
Priority                : CRITICAL

Recovery Actions:
1. Expedite material procurement
2. Increase manpower
3. Increase working hours
4. Prioritize critical-path activity
5. Coordinate successor activities

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🏢 Demo Project

The project includes a sample construction schedule: ConstructAI Building Control Demo

The schedule contains activities covering:

Site Mobilization · Excavation · PCC · Footing Reinforcement · Footing Concrete · Pedestal Reinforcement · Pedestal Concrete · Column Reinforcement · Column Concrete · Slab Reinforcement · Slab Concrete · Masonry · Electrical Rough-in · Plumbing Rough-in · Plastering · Flooring · False Ceiling · Painting · Final MEP Installation · Testing & Commissioning · Final Inspection & Handover

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🧪 Testing

The project contains test files for major project-control modules and MCP functionality, including:

• test_cpm.py
• test_delay.py
• test_delay_impact.py
• test_project_status.py
• test_project_risk.py
• test_schedule_recovery.py
• test_resource_bottleneck.py
• test_project_control_summary.py

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📁 Project Structure

ConstructAI/
│
├── ai_client.py
├── server.py
│
├── database.py
├── models.py
│
├── cpm.py
├── schedule.py
├── schedule_variance.py
├── forecast.py
│
├── activity_details.py
├── activity_dependencies.py
├── critical_activities.py
├── delayed_activities.py
├── find_activity.py
│
├── delay_analysis.py
├── delay_impact.py
│
├── recovery.py
├── recovery_impact.py
├── schedule_recovery.py
│
├── resource_bottleneck.py
├── project_risk_analysis.py
├── project_control.py
├── project_control_summary.py
├── project_status.py
├── recommendations.py
│
├── requirements.txt
├── README.md
└── .gitignore

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🚀 Installation

1. Clone the repository

git clone https://github.com/bilalgit/ConstructAI.git
cd ConstructAI

2. Create a virtual environment

python -m venv venv

Activate it on Windows:

venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Install Ollama

Install Ollama and download the Qwen3 model:

ollama pull qwen3:8b

5. Run ConstructAI

Start the MCP server and AI client according to the project configuration.

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💰 Cost

Item	Value
AI Model	Qwen3 8B
Inference	Local
API Cost	₹0

No paid AI inference API is required for the current setup.

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🎯 Project Objective

The objective of ConstructAI is to explore how Artificial Intelligence and Model Context Protocol can be applied to construction project management and project controls.

The project combines:

• Civil Engineering
• Construction Planning
• Critical Path Method
• Schedule Management
• Delay Analysis
• Risk Management
• Resource Management
• Artificial Intelligence
• MCP Tool Calling
• Local LLMs
• Database-driven project controls

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🔮 Future Development

Potential future improvements include:

• Construction cost control
• Quantity tracking
• Earned Value Management
• Resource leveling
• Progress forecasting
• Automated daily progress reports
• AI-generated weekly and monthly reports
• BIM integration
• Primavera P6 integration
• Power BI dashboards
• Construction document intelligence
• Multi-project portfolio monitoring

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👨‍💻 Author

Bilal

Civil Engineering | Construction Project Controls | AI Engineering

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⭐ If you find this project interesting, feel free to explore the repository.