mpesa-mcp

MCP server for East African fintech APIs — M-Pesa (Safaricom Daraja) and Africa's Talking

Give your AI agent the ability to trigger M-Pesa payments, check transaction status, send SMS, and top up airtime across 20+ African telecom networks.

Tested With

Code

claude-sonnet-5  (recommended — call get_model_hint() for guidance)
claude-opus-4-8  (for highest-accuracy compliance reasoning)

Claude Sonnet 5 (released June 30, 2026) finishes multi-step M-PESA workflows without stopping short and self-corrects tool-call errors without prompting. Terminal-Bench score 80.4% vs Sonnet 4.6's 67.0% — the benchmark most analogous to payment agent work.

Why this exists

M-Pesa processes more transactions per day than PayPal does in Africa. Africa's Talking reaches users in 20+ countries on basic phones via SMS and USSD. Neither has an MCP server.

This means every AI agent built today — Claude, GPT, Gemini, or any MCP-compatible runtime — cannot trigger an M-Pesa payment or send a Kiswahili SMS without custom integration work.

mpesa-mcp closes that gap in one pip install.

Tools

Tool	Description
`mpesa_stk_push`	Trigger STK Push payment prompt on customer's M-Pesa phone
`mpesa_stk_query`	Check status of an STK Push request
`mpesa_transaction_status`	Query any M-Pesa transaction by receipt number
`sms_send`	Send SMS to 1–1,000 recipients across African networks
`airtime_send`	Send airtime top-up to any subscriber (KES, NGN, GHS, UGX, etc.)

Coverage

M-Pesa: Kenya (Safaricom Daraja v3) — STK Push, C2B, transaction status
SMS/Airtime: Kenya, Nigeria, Ghana, Tanzania, Uganda, Rwanda, South Africa, and 15+ more via Africa's Talking

Glama (hosted MCP)

mpesa-mcp is available as a hosted MCP server on Glama:

Security — NSA MCP Guidance Compliant

mpesa-mcp was updated in response to NSA CSI U/OO/6030316-26 (May 2026) — the NSA Artificial Intelligence Security Center's Cybersecurity Information Sheet on Model Context Protocol security.

The implementation below documents compliance against the NSA's MCP security framework, control by control.

NSA Control	Implementation
Parameter validation	KE phone regex `^254[17]\d{8}$` + amount bounds [1–150,000 KES]
Audit logging	Structured log per tool call; phone numbers SHA-256 hashed
Token lifecycle	OAuth token cached with expiry; auto-refreshed
Error containment	Structured error dicts; no raw exception propagation
HTTPS enforcement	All Daraja API calls HTTPS-only
No hardcoded secrets	All credentials via environment variables

See SECURITY.md for the full compliance table.

Reference: NSA CSI_MCP_SECURITY.pdf — May 2026, UNCLASSIFIED

Install

Terminal

pip install mpesa-mcp

Or run directly with uvx:

bash

uvx mpesa-mcp

Configuration

Set these environment variables before starting the server:

bash

# M-Pesa (Safaricom Daraja)
MPESA_CONSUMER_KEY=your_consumer_key
MPESA_CONSUMER_SECRET=your_consumer_secret
MPESA_SHORTCODE=174379               # sandbox test shortcode
MPESA_PASSKEY=your_passkey
MPESA_CALLBACK_URL=https://yourdomain.com/mpesa/callback
MPESA_SANDBOX=true                   # set false for production

# Africa's Talking
AT_USERNAME=sandbox                  # your AT username (sandbox for testing)
AT_API_KEY=your_at_api_key

Sandbox credentials

M-Pesa sandbox: https://developer.safaricom.co.ke — create a free app to get test credentials.

Test shortcode: 174379
Test passkey: bfb279f9aa9bdbcf158e97dd71a467cd2e0c893059b10f78e6b72ada1ed2c919

Africa's Talking sandbox: https://account.africastalking.com — use username=sandbox, any API key.

Usage with Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

config.json

{
  "mcpServers": {
    "mpesa": {
      "command": "uvx",
      "args": ["mpesa-mcp"],
      "env": {
        "MPESA_CONSUMER_KEY": "your_key",
        "MPESA_CONSUMER_SECRET": "your_secret",
        "MPESA_SHORTCODE": "174379",
        "MPESA_PASSKEY": "your_passkey",
        "MPESA_CALLBACK_URL": "https://yourdomain.com/mpesa/callback",
        "MPESA_SANDBOX": "true",
        "AT_USERNAME": "sandbox",
        "AT_API_KEY": "your_at_key"
      }
    }
  }
}

Usage with Claude Code

Terminal

claude mcp add mpesa -- uvx mpesa-mcp

Set env vars in your shell before running claude.

Example prompts

Once connected, you can ask your AI agent:

"Send KES 500 STK Push to +254712345678 for order #1234"

"Check if the payment QKL8ABC123 has been received"

"Send an SMS to these 50 farmers with today's maize price: [list]"

"Top up KES 50 airtime for our field agents: [list of numbers]"

Real-world scenarios

Field agent payment dispatch

"Send KES 300 STK Push to each of these 12 field agents for today's data collection: [list]"

The agent triggers 12 sequential STK pushes, tracks each checkout_request_id, and polls for confirmation — without any code from you.

Farmer alert + airtime

"SMS these 200 Garissa farmers that the river is rising. Then top up KES 20 airtime each so they can call in reports."

One prompt → 200 SMS messages and 200 airtime top-ups across Safaricom, Airtel, and Telkom.

Payment reconciliation

"Check whether receipt OKL8M3B2HF was a successful payment and how much it was for"

Useful for support agents using Claude to verify M-Pesa transactions in real time.

Tool annotations

All tools declare MCP tool annotations so clients can gate calls appropriately:

Tool	readOnly	destructive	idempotent
`mpesa_stk_push`	❌	✅	❌
`mpesa_stk_query`	✅	❌	✅
`mpesa_transaction_status`	✅	❌	✅
`sms_send`	❌	✅	❌
`airtime_send`	❌	✅	❌

Claude Desktop and other MCP clients will request confirmation before triggering payment, SMS, or airtime operations.

Server discovery

Capabilities are advertised via .well-known/mcp.json — the emerging MCP Server Cards standard. Registries and browsers can index this server's tools without connecting to it.

bash

# Check capabilities
curl https://raw.githubusercontent.com/gabrielmahia/mpesa-mcp/main/.well-known/mcp.json

Testing and accuracy

The MCP ecosystem benchmark (CData, 2026) found most MCP servers accurate 60–75% of the time on complex queries — particularly silent failures on write operations and partial parameter application.

mpesa-mcp is tested against all three Kenyan phone number formats, boundary amount values, and missing optional fields:

bash

pytest tests/ -v  # run full suite
pytest tests/test_phone_formats.py  # format normalization
pytest tests/test_boundary_amounts.py  # min/max amount edge cases

Write operations (STK push, SMS, airtime) have explicit validation before any API call is made.

Ecosystem context — Mojaloop + MCP

Mojaloop (funded by the Gates Foundation) handles payment interoperability — connecting banks, mobile money wallets, and merchants across DFSPs in East Africa and beyond.

mpesa-mcp handles the AI agent tooling layer — enabling AI coding assistants to trigger and query M-Pesa payments programmatically.

These are complementary:

Mojaloop: the interoperability rails between financial providers
mpesa-mcp: the MCP interface layer that connects AI agents to those rails

See the Mojaloop documentation contribution for more on this pattern.

MCP vs A2A — two different protocols

mpesa-mcp implements MCP (Model Context Protocol) — how an AI agent talks to tools.

There is a complementary protocol, A2A (Agent-to-Agent), which handles how agents talk to each other. They solve different problems and work together:

MCP: Your AI agent → mpesa-mcp → Daraja API / Africa's Talking
A2A: Orchestrator agent ↔ payment sub-agent ↔ notification sub-agent

For most integrations you only need MCP. A2A becomes relevant when you're building multi-agent systems where a payment workflow coordinates with other specialized agents.

Development

bash

git clone https://github.com/gabrielmahia/mpesa-mcp
cd mpesa-mcp
pip install -e ".[dev]"
pytest tests/ -v

Security

Do not commit API keys. Use environment variables or a secrets manager.
Report vulnerabilities to: contact@aikungfu.dev

Research Context

MCP ecosystem benchmark (CData, 2026): Most MCP servers achieve 60-75% accuracy on complex queries. mpesa-mcp includes explicit validation and bounds checking to exceed this baseline.

Swahili AI accuracy (arXiv:2509.04516, 2025): AI models produce 4× more errors in Swahili than English. mpesa-mcp's Swahili-native tool descriptions are designed to minimize this gap for Swahili-speaking users by eliminating the translation step in tool selection.

MCP security research (arXiv:2603.18063, arXiv:2603.21642, 2026): Prompt injection via tool descriptions is the primary MCP attack vector. mpesa-mcp mitigates this through static, versioned tool descriptions and strict input validation.

Related infrastructure:

wapimaji-mcp — Kenya water/drought MCP
civic-agent-kit — Kenya civic data MCP
swahili-health-mcp — Kenya DHIS2 health data MCP
kenya-legal-rag — Kenya legal corpus MCP
Full portfolio: gabrielmahia.github.io

License

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Or watch this repo on GitHub for release notifications.

Sibling packages

Package	Install	Description
wapimaji-mcp	`pip install wapimaji-mcp`	Kenya drought intelligence MCP server
civic-agent-kit	`pip install civic-agent-kit`	East African civic AI SDK

Related packages

All MIT · All part of the East African civic AI stack

Package	Install	Description
wapimaji-mcp	`pip install wapimaji-mcp`	Kenya drought intelligence MCP server
kenya-health-mcp	`pip install kenya-health-mcp`	Kenya health data MCP — NHIF, facilities, maternal, rights
civic-agent-kit	`pip install civic-agent-kit`	East African civic AI SDK

Full portfolio: gabrielmahia.github.io

Part of the East Africa Coordination Stack

This MCP server is one of 32 tools in the Kenya coordination infrastructure. Connect it to africa-coord-bus — the coordination event bus that routes signals between domains automatically.

Terminal

pip install africa-coord-bus

All 32 servers: pypi.org/user/gmahia Live demo: coord-cascade-demo

IP & Collaboration

MIT licensed. Feedback via GitHub Issues only — pull requests are not accepted. Demo data is labeled DEMO and is not suitable for operational decisions. Full policy: docs/architecture/IP_POLICY.md. Security reports: see SECURITY.md.

Part of the East Africa coordination stack

Install & run: pip install reli-cli && reli list — 33 MCP servers on the official MCP Registry under io.github.gabrielmahia
Evaluate any model on Swahili agent tasks: kipimo · dataset · leaderboard
Coordinate across servers: africa-coord-bus — offline-first event bus with a built-in Kenya routing table
Datasets: huggingface.co/gmahia · Docs hub: nairobi-stack

Model-agnostic by design: closed APIs, open-weight models, and small distilled models are all first-class citizens.