In 2024-2025, three significant AI agent protocols emerged:
- MCP (Model Context Protocol) — Anthropic's open standard for tools and data
- A2A (Agent-to-Agent) — cross-vendor agent communication protocol
- Google ADK (Agent Development Kit) — production agent pipeline framework
Most developers picked one. Most regions had zero implementations of any.
I built all three — for East Africa — and I'm the first documented engineer in the region to do so.
Why All Three?
The ecosystem will consolidate, and first-mover implementations are valuable regardless of which wins. Being the reference for East Africa on all three means the region's infrastructure isn't locked to any single vendor's roadmap.
But practically: each genuinely solves a different problem.
MCP — For Wrapping Existing APIs
MCP is the right choice when wrapping APIs as tool calls an AI agent can invoke directly.
For East Africa:
pip install mpesa-mcp # M-PESA Daraja API
pip install wapimaji-mcp # Kenya water infrastructure
pip install swahili-health-mcp # DHIS2 health data
# Add to Claude
claude mcp add mpesa -- mpesa-mcp
claude mcp add water -- wapimaji-mcp
MCP's value: reducing integration friction per developer to near-zero. The institutional knowledge lives in the MCP server, not in every app built on top.
Result: mpesa-mcp — v0.1.9 on PyPI, 400+ downloads, 12 countries, first African payment API in the MCP ecosystem.
A2A — For Multi-Agent Coordination
A2A is the right choice when multiple specialized agents need to coordinate on complex tasks — negotiating, delegating, sharing context.
For Kenya's civic stack, this means budget accountability that needs a financial agent + legal agent + Swahili summarization agent working together. kenya-a2a handles the message routing and capability advertisement.
Google ADK — For Production Pipelines
ADK is the right choice for production-grade pipelines with evaluation and observability. kenya-adk runs multi-step Swahili advisory workflows with integrated quality evaluation.
The Swahili-First Architecture
All three implementations share one principle: tool descriptions are written in Kiswahili.
When an AI agent receives a Swahili instruction and selects tools, it matches against descriptions. English descriptions introduce a translation step — a failure mode. Swahili descriptions eliminate it:
{
"name": "mpesa_stk_push",
"description": "Anzisha malipo ya Lipa Na M-PESA. "
"Tumia wakati mtumiaji anataka kulipa kwa M-PESA.",
}
Status
| Protocol | Repo | Status |
|---|---|---|
| MCP | mpesa-mcp | v0.1.9 · PyPI · 400+ downloads |
| MCP | wapimaji-mcp, swahili-health-mcp, kenya-legal-rag | Live |
| A2A | kenya-a2a | Live |
| ADK | kenya-adk | Live |
All MIT licensed. All part of a 110+ tool East Africa portfolio.
The Kenya MCP Hub is a CLI registry for all servers:
pip install kenya-mcp-hub
kenya-mcp-hub list
Portfolio: gabrielmahia.github.io
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