mpesa-mcp
mpesa-mcp
MCP-Server für ostafrikanische Fintech-APIs – M-Pesa (Safaricom Daraja) und Africa's Talking
Geben Sie Ihrem KI-Agenten die Fähigkeit, M-Pesa-Zahlungen auszulösen, den Transaktionsstatus zu prüfen, SMS zu versenden und Guthaben in über 20 afrikanischen Telekommunikationsnetzen aufzuladen.
Warum existiert dieses Projekt?
M-Pesa verarbeitet in Afrika täglich mehr Transaktionen als PayPal. Africa's Talking erreicht Nutzer in über 20 Ländern auf einfachen Mobiltelefonen per SMS und USSD. Keiner von beiden verfügt über einen MCP-Server.
Das bedeutet, dass jeder heute entwickelte KI-Agent – Claude, GPT, Gemini oder eine andere MCP-kompatible Laufzeitumgebung – keine M-Pesa-Zahlung auslösen oder eine SMS auf Kiswahili senden kann, ohne dass benutzerdefinierte Integrationsarbeit geleistet wird.
mpesa-mcp schließt diese Lücke mit einem einzigen pip install.
Related MCP server: M-Pesa MCP Server
Tools
Tool | Beschreibung |
| Löst eine STK-Push-Zahlungsaufforderung auf dem M-Pesa-Telefon des Kunden aus |
| Prüft den Status einer STK-Push-Anfrage |
| Fragt jede M-Pesa-Transaktion anhand der Quittungsnummer ab |
| Sendet SMS an 1–1.000 Empfänger in afrikanischen Netzwerken |
| Sendet Guthabenaufladungen an jeden Teilnehmer (KES, NGN, GHS, UGX usw.) |
Abdeckung
M-Pesa: Kenia (Safaricom Daraja v3) – STK Push, C2B, Transaktionsstatus
SMS/Guthaben: Kenia, Nigeria, Ghana, Tansania, Uganda, Ruanda, Südafrika und über 15 weitere über Africa's Talking
Glama (gehostetes MCP)
mpesa-mcp ist als gehosteter MCP-Server auf Glama verfügbar:
Installation
pip install mpesa-mcpOder führen Sie es direkt mit uvx aus:
uvx mpesa-mcpKonfiguration
Setzen Sie diese Umgebungsvariablen, bevor Sie den Server starten:
# 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_keySandbox-Anmeldedaten
M-Pesa Sandbox: https://developer.safaricom.co.ke – erstellen Sie eine kostenlose App, um Test-Anmeldedaten zu erhalten.
Test-Kurzwahlnummer:
174379Test-Passkey:
bfb279f9aa9bdbcf158e97dd71a467cd2e0c893059b10f78e6b72ada1ed2c919
Africa's Talking Sandbox: https://account.africastalking.com – verwenden Sie username=sandbox und einen beliebigen API-Schlüssel.
Verwendung mit Claude Desktop
Fügen Sie dies zu ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) hinzu:
{
"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"
}
}
}
}Verwendung mit Claude Code
claude mcp add mpesa -- uvx mpesa-mcpSetzen Sie die Umgebungsvariablen in Ihrer Shell, bevor Sie claude ausführen.
Beispiel-Prompts
Sobald die Verbindung hergestellt ist, können Sie Ihren KI-Agenten fragen:
"Sende eine KES 500 STK-Push-Anfrage an +254712345678 für Bestellung #1234"
"Prüfe, ob die Zahlung QKL8ABC123 eingegangen ist"
"Sende eine SMS an diese 5 farmers mit dem heutigen Maispreis: [Liste]"
"Lade KES 50 Guthaben für unsere Außendienstmitarbeiter auf: [Liste der Nummern]"
Praxisbeispiele
Zahlungsabwicklung für Außendienstmitarbeiter
"Sende eine KES 300 STK-Push-Anfrage an jeden dieser 12 Außendienstmitarbeiter für die heutige Datenerfassung: [Liste]"
Der Agent löst 12 aufeinanderfolgende STK-Push-Anfragen aus, verfolgt jede checkout_request_id und fragt den Status zur Bestätigung ab – ohne dass Sie Code schreiben müssen.
Farmer-Alarm + Guthaben
"Sende eine SMS an diese 200 Farmer in Garissa, dass der Fluss steigt. Lade dann jedem 20 KES Guthaben auf, damit sie Berichte abgeben können."
Ein Prompt → 200 SMS-Nachrichten und 200 Guthabenaufladungen über Safaricom, Airtel und Telkom.
Zahlungsabgleich
"Prüfe, ob die Quittung OKL8M3B2HF eine erfolgreiche Zahlung war und wie hoch der Betrag war"
Nützlich für Support-Mitarbeiter, die Claude verwenden, um M-Pesa-Transaktionen in Echtzeit zu verifizieren.
Tool-Annotationen
Alle Tools deklarieren MCP-Tool-Annotationen, damit Clients Aufrufe entsprechend einschränken können:
Tool | readOnly | destructive | idempotent |
| ❌ | ✅ | ❌ |
| ✅ | ❌ | ✅ |
| ✅ | ❌ | ✅ |
| ❌ | ✅ | ❌ |
| ❌ | ✅ | ❌ |
Claude Desktop und andere MCP-Clients fordern eine Bestätigung an, bevor sie Zahlungs-, SMS- oder Guthabenoperationen auslösen.
Server-Erkennung
Funktionen werden über .well-known/mcp.json beworben – dem aufkommenden Standard für MCP-Server-Karten. Registries und Browser können die Tools dieses Servers indizieren, ohne eine Verbindung zu ihm herzustellen.
# Check capabilities
curl https://raw.githubusercontent.com/gabrielmahia/mpesa-mcp/main/.well-known/mcp.jsonTests und Genauigkeit
Der MCP-Ökosystem-Benchmark (CData, 2026) ergab, dass die meisten MCP-Server bei komplexen Abfragen zu 60–75 % genau sind – insbesondere bei stillen Fehlern bei Schreibvorgängen und teilweiser Parameteranwendung.
mpesa-mcp wurde gegen alle drei kenianischen Telefonnummernformate, Grenzwerte für Beträge und fehlende optionale Felder getestet:
pytest tests/ -v # run full suite
pytest tests/test_phone_formats.py # format normalization
pytest tests/test_boundary_amounts.py # min/max amount edge casesSchreibvorgänge (STK-Push, SMS, Guthaben) verfügen über eine explizite Validierung, bevor ein API-Aufruf getätigt wird.
Ökosystem-Kontext — Mojaloop + MCP
Mojaloop (finanziert von der Gates Foundation) kümmert sich um die Zahlungs-Interoperabilität – die Verbindung von Banken, mobilen Geldbörsen und Händlern über DFSPs in Ostafrika und darüber hinaus.
mpesa-mcp kümmert sich um die KI-Agenten-Tooling-Ebene – und ermöglicht es KI-Programmierassistenten, M-Pesa-Zahlungen programmgesteuert auszulösen und abzufragen.
Diese ergänzen sich:
Mojaloop: die Interoperabilitätsschienen zwischen Finanzanbietern
mpesa-mcp: die MCP-Schnittstellenebene, die KI-Agenten mit diesen Schienen verbindet
Siehe den Mojaloop-Dokumentationsbeitrag für mehr Informationen zu diesem Muster.
MCP vs. A2A — zwei verschiedene Protokolle
mpesa-mcp implementiert MCP (Model Context Protocol) – wie ein KI-Agent mit Tools spricht.
Es gibt ein ergänzendes Protokoll, A2A (Agent-to-Agent), das regelt, wie Agenten untereinander kommunizieren. Sie lösen unterschiedliche Probleme und arbeiten zusammen:
MCP: Ihr KI-Agent → mpesa-mcp → Daraja API / Africa's Talking
A2A: Orchestrator-Agent ↔ Zahlungs-Sub-Agent ↔ Benachrichtigungs-Sub-Agent
Für die meisten Integrationen benötigen Sie nur MCP. A2A wird relevant, wenn Sie Multi-Agenten-Systeme aufbauen, bei denen ein Zahlungs-Workflow mit anderen spezialisierten Agenten koordiniert wird.
Entwicklung
git clone https://github.com/gabrielmahia/mpesa-mcp
cd mpesa-mcp
pip install -e ".[dev]"
pytest tests/ -vSicherheit
Committen Sie keine API-Schlüssel. Verwenden Sie Umgebungsvariablen oder einen Secrets-Manager. Melden Sie Sicherheitslücken an: contact@aikungfu.dev
Lizenz
MIT — © 2026 Gabriel Mahia
Bleiben Sie auf dem Laufenden
Erhalten Sie Benachrichtigungen über neue Releases und Entwicklungen bei ostafrikanischen APIs: Updates abonnieren →
Oder beobachten Sie dieses Repository auf GitHub für Release-Benachrichtigungen.
Verwandte Pakete
Paket | Installation | Beschreibung |
| MCP-Server für Dürre-Intelligenz in Kenia | |
| Ostafrikanisches Civic-KI-SDK |
Zugehörige Pakete
Alle MIT · Alle Teil des ostafrikanischen Civic-KI-Stacks
Paket | Installation | Beschreibung |
| MCP-Server für Dürre-Intelligenz in Kenia | |
| Kenia-Gesundheitsdaten-MCP – NHIF, Einrichtungen, Mütter, Rechte | |
| Ostafrikanisches Civic-KI-SDK |
Gesamtportfolio: gabrielmahia.github.io
Available Tools
5 toolsairtime_sendSend AirtimeADestructive
Send airtime top-up to any MTN/Safaricom/Airtel/Vodafone subscriber. Common use: NGO field incentives, survey rewards, agent payouts. No real airtime sent in sandbox mode.
| Name | Required | Description | Default |
|---|---|---|---|
| phone | Yes | Recipient phone in E.164 format e.g. '+254712345678' | |
| amount | Yes | Amount as string e.g. '50' (KES 50). Minimum KES 10 in production. | |
| currency_code | No | ISO currency code: KES, NGN, GHS, UGX, TZS, RWF, ZAR | KES |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructive/destructiveHint=true. Description adds valuable sandbox behavior disclosure. Does not discuss other aspects like auth or rate limits, but the added sandbox note is useful beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each adding distinct value: action, use cases, sandbox note. No fluff, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (return values not needed), the description covers purpose, common usage, and sandbox behavior. Lacks prerequisites or error scenarios, but sufficient for a simple tool with good annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and already describes each parameter in detail (including minimum amount in production). Description does not add new parameter information beyond what's in the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action (send airtime top-up) and target (specific network subscribers). Common use cases provided. Distinguishes from siblings like mpesa_stk_push which are for money transfers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Lists common use cases (NGO incentives, survey rewards, agent payouts) and mentions sandbox mode behavior. Does not explicitly compare to alternatives, but given sibling tools, context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mpesa_stk_pushM-Pesa STK PushADestructive
Trigger an M-Pesa STK Push — sends a payment prompt to the customer's phone. The customer enters their M-Pesa PIN to complete payment. Returns a CheckoutRequestID to track the transaction with mpesa_stk_query. Async: use mpesa_stk_query after 10-30 seconds to check completion.
| Name | Required | Description | Default |
|---|---|---|---|
| phone | Yes | Customer phone number (any Kenyan format: +254..., 07..., 254...) | |
| amount | Yes | Amount in KES (whole number, minimum 1) | |
| account_ref | Yes | Account reference shown to customer on their phone (max 12 chars) | |
| description | No | Transaction description (max 13 chars) | Payment |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond annotations: it explains that the tool is async, that the customer enters their PIN to complete payment, and that a CheckoutRequestID is returned for follow-up. This aligns with destructiveHint=true and provides useful actionable information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with four short sentences, all of which provide necessary information. It front-loads the primary action and sequentially covers process, return value, and follow-up. There is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential aspects of a payment initiation tool: what it does (trigger STK push), the user interaction (customer enters PIN), the result (CheckoutRequestID), and the asynchronous follow-up (use mpesa_stk_query after 10-30 seconds). With an output schema present, the description does not need to detail return fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all parameters. The tool description does not add additional meaning beyond the schema (e.g., no examples or format clarification). Baseline 3 applies as schema already documents parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool triggers an M-Pesa STK Push, sends a payment prompt to the customer's phone, and returns a CheckoutRequestID for tracking. It distinguishes itself from sibling tools like mpesa_stk_query by noting that the query tool is for checking completion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the sibling tool mpesa_stk_query (after 10-30 seconds) to check completion. It implies that this tool is for initiating payments, but does not explicitly state when not to use it or mention alternatives like airtime_send.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mpesa_stk_queryM-Pesa STK QueryARead-onlyIdempotent
Check the status of an STK Push request. Poll this 10-30 seconds after calling mpesa_stk_push. ResultCode 0 = success, 1032 = cancelled by user, 1037 = timed out.
| Name | Required | Description | Default |
|---|---|---|---|
| checkout_request_id | Yes | CheckoutRequestID from mpesa_stk_push response |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, idempotentHint), the description adds polling timing and result code meanings, disclosing behavioral traits like non-immediate result and cancellation handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, each essential: purpose, timing advice, and result interpretation. No extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and existing output schema, the description fully covers polling strategy, result codes, and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description merely restates the parameter's purpose ('CheckoutRequestID from mpesa_stk_push response') without adding additional meaning or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Check the status of an STK Push request' with a specific verb and resource, distinguishing it from siblings like mpesa_stk_push (initiates) and mpesa_transaction_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to poll 10-30 seconds after calling mpesa_stk_push, and interprets result codes (0=success, 1032=cancelled, 1037=timed out), providing clear when-to-use and expected outcomes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mpesa_transaction_statusM-Pesa Transaction StatusARead-onlyIdempotent
Query the status of any M-Pesa transaction by receipt number. Requires MPESA_INITIATOR_NAME and MPESA_SECURITY_CREDENTIAL env vars.
| Name | Required | Description | Default |
|---|---|---|---|
| transaction_id | Yes | M-Pesa receipt number e.g. QKL8XXXXXX |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive. Description adds valuable prerequisite info (env vars) beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, both essential. Front-loaded with purpose, then prerequisite. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simple tool with output schema and rich annotations, description is mostly complete. Missing rate limits or side-effect details, but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers 100% of parameter with example. Description adds no new semantics, so baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific verb (Query) and resource (transaction status) with receipt number. Distinguishes from sibling tools like airtime_send and sms_send.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions required environment variables but does not explicitly state when to use this tool vs alternatives like mpesa_stk_query. Usage is implied by name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sms_sendSend SMSADestructive
Send SMS to one or many recipients via Africa's Talking. Supports up to 1,000 recipients per call. Works across Kenya, Nigeria, Ghana, Tanzania, Uganda, and 15+ African markets. Returns per-recipient status and cost.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | SMS message text. Unicode supported (Kiswahili, etc.) | |
| sender_id | No | Optional pre-registered alphanumeric sender ID | |
| recipients | Yes | List of phone numbers in E.164 format e.g. ['+254712345678'] |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and idempotentHint=false. The description adds valuable behavioral details: the maximum recipient limit, geographic coverage, and that it returns per-recipient status and cost. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, each serving a distinct purpose: what the tool does, its capacity and scope, and its return value. No wasted words, and the most critical information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three well-documented parameters and an existing output schema, the description covers the essential aspects: operation, capacity, geographic scope, and return format. It is sufficiently complete for an agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema itself clearly documents all three parameters. The description adds no additional parameter-level meaning beyond what is in the schema (e.g., it mentions Unicode support which is already in the message description). Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool sends SMS via Africa's Talking, specifies the maximum recipients (1,000), mentions geographic coverage, and indicates return of per-recipient status and cost, distinguishing it from sibling tools like airtime_send or mpesa_stk_push which perform different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (sending SMS to one or many recipients) and includes practical limits (1,000 recipients). It does not explicitly mention when not to use it or compare to alternatives, but the sibling tools are sufficiently different that no confusion arises.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
5 tool updates
v0.1.0- First observed
airtime_send - First observed
mpesa_stk_push - First observed
mpesa_stk_query - First observed
mpesa_transaction_status - First observed
sms_send
TDQS
Scored across 5 tools
Each tool targets a distinct function: airtime sending, STK push initiation, STK push status query, transaction status by receipt, and SMS sending. There is no overlap or ambiguity.
Most tools follow a verb_noun or noun_verb pattern (e.g., airtime_send, sms_send, mpesa_stk_push), but mpesa_transaction_status lacks a verb, breaking the pattern slightly.
With 5 tools, the server is well-scoped for its purpose, covering core M-Pesa and SMS operations without being too few or too many.
The set covers STK push initiation/query and basic transaction status, but lacks airtime status, B2C/C2B transfers, or account balance queries, leaving notable gaps for a full M-Pesa integration.
Maintenance
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Related MCP Servers
FlicenseNot gradedqualityDmaintenanceOpen-source MCP server that streamlines payment integration for AI agents and financial apps in Africa, providing unified tools for providers like M-Pesa.1-- FlicenseNot gradedqualityCmaintenanceAn experimental MCP server that lets AI agents interact with guarded payment workflows through typed tools, enabling safe agent-assisted payments with M-Pesa and mock Airtel Money.2-
- FlicenseNot gradedqualityDmaintenanceA Model Context Protocol (MCP) server that integrates Safaricom's M-PESA Daraja API with Claude, enabling natural language payment processing and real-time transaction notifications.3-
- AlicenseCqualityDmaintenanceAn MCP server that enables AI assistants to interact with Interswitch APIs for payments, transfers, VAS, cardless paycodes, Transaction Search, Card 360, lending, payouts, agency banking, and fintech card-processing utilities.7458 npm1MIT