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mpesa-mcp

Name: mpesa-mcp
Author: gabrielmahia

by gabrielmahia

Overview Schema Source Related Servers Discussions Admin

Python

Remote

mpesa-mcp

東アフリカのフィンテックAPI用MCPサーバー — M-Pesa (Safaricom Daraja) および Africa's Talking

AIエージェントに、M-Pesa決済のトリガー、取引状況の確認、SMS送信、および20以上のアフリカの通信ネットワーク間での通信料チャージ機能を提供します。

Tests PyPI License: MIT Glama Score Glama

mpesa-mcp MCP server

なぜこれが必要なのか

M-Pesaは、アフリカにおいてPayPalよりも1日あたりの取引処理数が多いサービスです。Africa's Talkingは、SMSやUSSDを通じて20カ国以上のベーシックフォンユーザーにリーチできます。しかし、どちらもMCPサーバーを提供していません。

つまり、現在構築されているすべてのAIエージェント（Claude、GPT、Gemini、またはMCP互換ランタイム）は、カスタム統合作業なしではM-Pesa決済をトリガーしたり、スワヒリ語のSMSを送信したりすることができません。

mpesa-mcp は、pip install 一つでそのギャップを埋めます。

Related MCP server: M-Pesa MCP Server

ツール

ツール	説明
`mpesa_stk_push`	顧客のM-Pesa電話機でSTKプッシュ決済プロンプトをトリガーする
`mpesa_stk_query`	STKプッシュリクエストのステータスを確認する
`mpesa_transaction_status`	レシート番号でM-Pesaの取引を照会する
`sms_send`	アフリカのネットワーク全体で1〜1,000人の受信者にSMSを送信する
`airtime_send`	あらゆる加入者に通信料をチャージする (KES, NGN, GHS, UGXなど)

対応範囲

M-Pesa: ケニア (Safaricom Daraja v3) — STKプッシュ、C2B、取引ステータス
SMS/通信料: ケニア、ナイジェリア、ガーナ、タンザニア、ウガンダ、ルワンダ、南アフリカなど、Africa's Talking経由で15カ国以上

Glama (ホスト型MCP)

mpesa-mcpは、Glama 上でホスト型MCPサーバーとして利用可能です：

mpesa-mcp MCP server mpesa-mcp score

インストール

pip install mpesa-mcp

または uvx で直接実行します：

uvx mpesa-mcp

設定

サーバーを起動する前に、以下の環境変数を設定してください：

# 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

サンドボックス認証情報

M-Pesaサンドボックス: https://developer.safaricom.co.ke — 無料アプリを作成してテスト用認証情報を取得してください。

テスト用ショートコード: 174379
テスト用パスキー: bfb279f9aa9bdbcf158e97dd71a467cd2e0c893059b10f78e6b72ada1ed2c919

Africa's Talkingサンドボックス: https://account.africastalking.com — username=sandbox を使用し、APIキーは何でも構いません。

Claude Desktopでの使用方法

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) に追加してください：

{
  "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"
      }
    }
  }
}

Claude Codeでの使用方法

claude mcp add mpesa -- uvx mpesa-mcp

claude を実行する前に、シェルで環境変数を設定してください。

プロンプト例

接続後、AIエージェントに以下のように依頼できます：

"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]"

実世界のシナリオ

フィールドエージェントへの支払い送金

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

エージェントは12件のSTKプッシュを順次トリガーし、各 checkout_request_id を追跡して確認をポーリングします。ユーザー側でコードを書く必要はありません。

農家へのアラート + 通信料チャージ

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

1つのプロンプトで、Safaricom、Airtel、Telkom全体で200件のSMS送信と200件の通信料チャージを行います。

支払い照合

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

Claudeを使用してM-Pesaの取引をリアルタイムで検証するサポートエージェントに役立ちます。

ツールのアノテーション

すべてのツールは MCPツールアノテーションを宣言しているため、クライアントは適切に呼び出しを制御できます：

ツール	readOnly	destructive	idempotent
`mpesa_stk_push`	❌	✅	❌
`mpesa_stk_query`	✅	❌	✅
`mpesa_transaction_status`	✅	❌	✅
`sms_send`	❌	✅	❌
`airtime_send`	❌	✅	❌

Claude Desktopおよびその他のMCPクライアントは、支払い、SMS、または通信料操作をトリガーする前に確認を求めます。

サーバー検出

機能は、新しいMCPサーバーカード標準である .well-known/mcp.json を通じてアドバタイズされます。レジストリやブラウザは、サーバーに接続することなく、このサーバーのツールをインデックス化できます。

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

テストと精度

MCPエコシステムのベンチマーク (CData, 2026) によると、ほとんどのMCPサーバーは複雑なクエリに対して60〜75%の精度であり、特に書き込み操作のサイレントエラーやパラメータの不完全な適用が課題となっています。

mpesa-mcpは、3つのケニアの電話番号形式すべて、境界値の金額、および欠落しているオプションフィールドに対してテストされています：

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

書き込み操作（STKプッシュ、SMS、通信料）は、API呼び出しが行われる前に明示的な検証が行われます。

エコシステムの背景 — Mojaloop + MCP

Mojaloop (ゲイツ財団が出資) は、東アフリカおよびそれ以外の地域のDFSP間で銀行、モバイルマネーウォレット、加盟店を接続する、決済の相互運用性を扱います。

mpesa-mcp は、AIエージェントのツールレイヤーを扱います。これにより、AIコーディングアシスタントがプログラムでM-Pesa決済をトリガーおよび照会できるようになります。

これらは補完的な関係にあります：

Mojaloop: 金融プロバイダー間の相互運用性レール
mpesa-mcp: AIエージェントをそれらのレールに接続するMCPインターフェースレイヤー

このパターンの詳細については、Mojaloopドキュメントへの貢献を参照してください。

MCP vs A2A — 2つの異なるプロトコル

mpesa-mcpは、AIエージェントがツールとどのように対話するかを定義する MCP (Model Context Protocol) を実装しています。

これとは別に、エージェント同士がどのように対話するかを処理する補完的なプロトコル A2A (Agent-to-Agent) があります。これらは異なる問題を解決し、連携して機能します：

MCP: AIエージェント → mpesa-mcp → Daraja API / Africa's Talking
A2A: オーケストレーターエージェント ↔ 支払いサブエージェント ↔ 通知サブエージェント

ほとんどの統合ではMCPのみで十分です。A2Aは、支払いワークフローが他の専門エージェントと調整を行うマルチエージェントシステムを構築する場合に関連してきます。

開発

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

セキュリティ

APIキーをコミットしないでください。環境変数またはシークレットマネージャーを使用してください。脆弱性の報告先: contact@aikungfu.dev

ライセンス

Available Tools

5 tools

airtime_sendSend AirtimeA

Destructive

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.

ParametersJSON Schema

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

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.2/5.0

Behavior4/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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 PushA

Destructive

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.

ParametersJSON Schema

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

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.5/5.0

Behavior5/5

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.

Conciseness5/5

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.

Completeness5/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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 QueryA

Read-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.

ParametersJSON Schema

Name	Required	Description	Default
`checkout_request_id`	Yes	CheckoutRequestID from mpesa_stk_push response

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.7/5.0

Behavior5/5

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.

Conciseness5/5

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.

Completeness5/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines5/5

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 StatusA

Read-onlyIdempotent

Query the status of any M-Pesa transaction by receipt number. Requires MPESA_INITIATOR_NAME and MPESA_SECURITY_CREDENTIAL env vars.

ParametersJSON Schema

Name	Required	Description	Default
`transaction_id`	Yes	M-Pesa receipt number e.g. QKL8XXXXXX

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4/5.0

Behavior4/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines3/5

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 SMSA

Destructive

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.

ParametersJSON Schema

Name	Required	Description
`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

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.3/5.0

Behavior4/5

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.

Conciseness5/5

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.

Completeness5/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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 updatesv0.1.0Apr 27, 2026
- First observedairtime_send
- First observedmpesa_stk_push
- First observedmpesa_stk_query
- First observedmpesa_transaction_status
- First observedsms_send

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored 2026-06-04 05:45 across 5 tools

Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count5/5

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.

Completeness3/5

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

ActivityActive

ResponsivenessSlow

Resources

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D
maintenance
A 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.
Updated 4 months ago (2026-05-26 15:47 UTC)
3
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Interswitch MCP Server
Finance Payments & Billing
Dairus01
A
license
C
quality
D
maintenance
An 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.
Updated 4 months ago (2026-05-07 01:36 UTC)
74
58 npm
1
MIT

パッケージ	インストール	説明
wapimaji-mcp	`pip install wapimaji-mcp`	ケニアの干ばつインテリジェンスMCPサーバー
civic-agent-kit	`pip install civic-agent-kit`	東アフリカの市民AI SDK

パッケージ	インストール	説明
wapimaji-mcp	`pip install wapimaji-mcp`	ケニアの干ばつインテリジェンスMCPサーバー
kenya-health-mcp	`pip install kenya-health-mcp`	ケニアの健康データMCP — NHIF、施設、母子保健、権利
civic-agent-kit	`pip install civic-agent-kit`	東アフリカの市民AI SDK

mpesa-mcp

なぜこれが必要なのか

ツール

対応範囲

Glama (ホスト型MCP)

インストール

設定

サンドボックス認証情報

Claude Desktopでの使用方法

Claude Codeでの使用方法

プロンプト例

実世界のシナリオ

ツールのアノテーション

サーバー検出

テストと精度

エコシステムの背景 — Mojaloop + MCP

MCP vs A2A — 2つの異なるプロトコル

開発

セキュリティ

ライセンス

最新情報の入手

関連パッケージ

関連パッケージ

Available Tools

Output Schema

Output Schema

Output Schema

Output Schema

Output Schema

Tool Schema Changelog

Maintenance

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