UBI-MCP-server-

This MCP Server for University Business Incubators (UBIs) and their clusters aids their performance analyses and assessments( Survivability, Sustainability and Structural rigidity), socio-human structural analysis and dynamic capabilities based on: Mixed Methods Strong Structuration Theory by Ademola Taiwo.

README.md

University Business Incubator Analysis Tool:

A comprehensive MCP (Model Context Protocol) tool for analyzing university business incubators from three complementary theoretical perspectives.

Overview This tool provides sophisticated analysis of university business incubators by integrating:

Business Incubator Performance Analysis:

Quantitative KPI analysis including occupancy rates, graduation rates, job creation, and revenue generation Socio-Structuration Analysis: Based on Giddens’ Structuration Theory, examining the duality of structure and agency Agentic Processes Analysis: Analyzing entrepreneurial agency capabilities including intentionality, forethought, self-reactiveness, and self-reflectiveness.

Features:

Synthetic Data Generation: Generate realistic incubator performance data, structuration contexts, and entrepreneur profiles.

Multi-dimensional Analysis: Analyze incubators from performance, structural, and agency perspectives.

Integrated Reporting: Generate comprehensive reports combining all three analytical perspectives.

Flexible Output: Support for JSON, Markdown, and HTML report formats Temporal Analysis: Track structural evolution and performance trends over time.

Installation

pip install pandas numpy scipy

Quick Start: Open the zip folder, navigate to the University_incubator_analysis file. From university_incubator_analysis import ( generate_incubator_data, analyze_performance, generate_structuration_contexts, analyze_structuration, generate_entrepreneur_profiles, analyze_agency, generate_comprehensive_report )

Generate synthetic data for the number of incubator(s) (e.g. 10 incubators, 12 time periods).

performance_data = generate_incubator_data(num_incubators=10, time_periods=12, seed=42)

Analyze performance

performance_analysis = analyze_performance(performance_data) print(f"Average graduati>{performance_analysis['kpi_analysis']['success_metrics']['average_graduati>:.1%}")

Generate and analyze structuration contexts

incubator_ids = performance_data['incubator_id'].unique().tolist() c>= generate_structurati>=42) structurati>= analyze_structurati>0])

Generate and analyze entrepreneur profiles

profiles = generate_entrepreneur_profiles(50, incubator_ids, seed=42) agency_analysis = analyze_agency(profiles, c>0])

Generate comprehensive report

report = generate_comprehensive_report( performance_data, performance_analysis, contexts, structuration_analysis, profiles, agency_analysis, output_format="json" )

print("Report generated successfully!") print(f"Executive Summary: {report['executive_summary']['overview']}")

Core Components

1. Performance Analysis Analyzes incubator KPIs including: - Occupancy and capacity metrics - Startup flow (admissions, graduations, failures) - Success metrics (graduation rate, survival rate) - Economic impact (jobs created, revenue, funding) - Efficiency analysis - Trend analysis - Comparative benchmarking

from university_incubator_analysis import analyze_performance

results = analyze_performance(data) print(results['kpi_analysis']) print(results['trend_analysis']) print(results['insights'])

2. Structuration Analysis Based on Giddens’ Structuration Theory, analyzes: - Signification: Meaning-making structures, rules, norms - Domination: Power relations, resource allocation - Legitimation: Normative orders, evaluation criteria - Structure-Agency Duality: How structures enable and constrain agency - Structuration Processes: Reproduction and transformation

from university_incubator_analysis import analyze_structuration

results = analyze_structuration(context) print(results['structural_analysis']) print(results['duality_analysis']) print(results['structuration_processes']) 3. Agency Analysis Analyzes entrepreneurial agency through four dimensions: - Intentionality: Goal clarity, strategic planning, commitment - Forethought: Future orientation, scenario planning, risk assessment - Self-Reactiveness: Adaptability, course correction, resource seeking - Self-Reflectiveness: Metacognition, learning orientation, feedback integration

from university_incubator_analysis import analyze_agency

results = analyze_agency(profiles) print(results['capability_analysis']) print(results['typology']) print(results['success_correlations']) 4. Comprehensive Reporting Generates integrated reports combining all perspectives:

from university_incubator_analysis import generate_comprehensive_report

JSON format (default)

report = generate_comprehensive_report( performance_data, performance_analysis, output_format="json" )

Markdown format

markdown_report = generate_comprehensive_report( performance_data, performance_analysis, structurati>=contexts, structurati>=structuration_analysis, entrepreneur_profiles=profiles, agency_analysis=agency_analysis, output_format="markdown" ) Data Models Incubator Performance Metrics Capacity and occupancy Startup flow metrics Success indicators Economic impact measures Input metrics (resources, services) Output metrics (outcomes, impact) Structuration Context Signification structures (rules, norms, meanings) Domination structures (power, resources) Legitimation structures (norms, sanctions, rewards) Agency manifestations Structuration dynamics Entrepreneur Profile Agentic capabilities (four dimensions) Embedded constraints Agency-structure interactions Success indicators Theoretical Background Giddens’ Structuration Theory The tool operationalizes Giddens’ concept of the duality of structure: - Structure: Rules and resources that enable and constrain action - Agency: Capacity of actors to make independent choices - Duality: Structure is both medium and outcome of agency

Three dimensions of structure: 1. Signification: Communication, meaning-making 2. Domination: Power, resource allocation 3. Legitimation: Normative orders, moral frameworks

Agentic Processes Based on social cognitive theory, analyzes: - Intentionality: Goal-directed behavior - Forethought: Anticipatory capability - Self-Reactiveness: Adaptive monitoring - Self-Reflectiveness: Metacognitive capability

Use Cases Incubator Management: Identify areas for improvement in operations and support services Policy Making: Understand how policies and structures affect entrepreneurial outcomes Research: Analyze structure-agency dynamics in entrepreneurial ecosystems Benchmarking: Compare performance across multiple incubators Program Evaluation: Assess effectiveness of incubator programs Testing Run the test suite:

pytest test_university_incubator_analysis.py -v Advanced Usage Temporal Analysis

Generate data over time

data = generate_incubator_data(num_incubators=5, time_periods=20)

Analyze trends

analysis = analyze_performance(data) trends = analysis['trend_analysis']

Analyze structural evolution

c>= [generate_structurati>'INC_001'])[0] for _ in range(5)] structurati>= analyze_structurati>0], temporal_data=contexts_over_time) print(structurati>'temporal_dynamics']) Custom Analysis from university_incubator_analysis import PerformanceAnalyzer, StructurationAnalyzer, AgencyAnalyzer

Use analyzers directly for custom workflows

perf_analyzer = PerformanceAnalyzer() struct_analyzer = StructurationAnalyzer() agency_analyzer = AgencyAnalyzer()

Perform custom analyses

custom_results = perf_analyzer._analyze_efficiency(data) Data Format Performance Data DataFrame Required columns: - incubator_id: Unique identifier - period: Time period (datetime) - occupancy_rate: Float (0-1) - graduation_rate: Float (0-1) - survival_rate: Float (0-1) - jobs_created: Integer - total_revenue_generated: Float - total_funding_raised: Float

Contributing Contributions welcome! Areas for enhancement: - Additional visualization generation - Machine learning models for prediction - Real-time data integration - Additional theoretical perspectives

License MIT License AdbatomIT Consulting 2025

Citation If you use this tool in research, please cite:

University Incubator Analysis Tool (2025) A comprehensive tool for multi-perspective analysis of business incubators created by Ademola O. TAIWO Contact: adbatomit@proton.me ademolataiwomba@gmail.com For questions and feedback, please open an issue on the repository.

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