Metadata-Version: 2.4
Name: mkopo-mcp
Version: 0.1.0
Summary: MCP server for alternative credit scoring in Kenya — M-PESA-based behavioral signals
Author-email: Gabriel Mahia <contact@aikungfu.dev>
License: MIT
Project-URL: Homepage, https://github.com/gabrielmahia/mkopo-mcp
Project-URL: Repository, https://github.com/gabrielmahia/mkopo-mcp
Project-URL: Issues, https://github.com/gabrielmahia/mkopo-mcp/issues
Keywords: mcp,credit,kenya,africa,mpesa,alternative-credit,fintech,mkopo
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Office/Business :: Financial
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: fastmcp>=2.0.0
Dynamic: license-file

# 💳 mkopo-mcp — Alternative Credit Scoring MCP Server

**First alternative credit scoring MCP server for East Africa.**

70%+ of Kenyan adults are "credit invisible" — no formal credit history means no access to capital. M-PESA is a de facto financial history record that predicts repayment behaviour. mkopo-mcp makes that intelligence accessible to AI agents.

## The Structural Problem

In mature economies, credit bureaus have 30+ years of credit card, mortgage, and auto loan data per person. That data machine took 50 years to build. In Kenya, most people's financial lives happen in cash and mobile money — invisible to formal credit systems.

**M-PESA is the credit bureau that doesn't know it is one.**

- Regular income deposits → income stability
- Utility payment regularity → discipline signal
- Savings behaviour (M-Shwari, chama) → future orientation
- Fuliza usage ratio → short-term distress indicator
- Business Paybill receipts → verifiable commercial activity

## Tools

| Tool | What it does |
|------|-------------|
| `alternative_credit_score` | Score from M-PESA behavioural signals (300–850 scale) |
| `mpesa_creditworthiness` | Analyse inflow/outflow patterns for loan capacity |
| `credit_report_summary` | Generate structured report like a loan officer would review |
| `loan_eligibility` | Match to appropriate Kenya lender types |
| `credit_improvement_tips` | Personalised steps to improve credit tier |

## Quick Start

```bash
pip install mkopo-mcp       # coming soon to PyPI
mkopo-mcp                   # starts on stdio
```

## Research Basis

- World Bank "Expanding Access to Finance" (2022)
- Breza & Kinnan "Measuring the Equilibrium Impacts of Credit" (2021)
- CBK Prudential Guidelines (2022)
- Kenya CRB Act (Cap. 44A)

⚠️ DEMO data — not a real CRB product. Consult Metropol or CRB Africa for official reports.

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*© 2026 Gabriel Mahia / AI Kung Fu LLC · MIT License*
