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14 stars PythonOthers Updated Sep 2, 2025

Documentation

Daraja MCP

> 🚨 Important Notice: Repository Moved

>

> This project has moved to a new repository. If you're looking to contribute or access the latest version, please visit:

>

> https://github.com/paylinkmcp/paylink

A Model Context Protocol (MCP) server designed to integrate AI applications with Safaricom's Daraja API, enabling seamless interaction with M-Pesa services.

> ⚠️ Warning: Not Production Ready

>

> This project is currently in development and is not recommended for production use. It's designed for:

>

> - Learning and experimentation

> - Development and testing environments

> - Proof of concept implementations

>

> For production use, please ensure:

>

> - Thorough security testing

> - Proper error handling

> - Complete implementation of all planned features

> - Compliance with Safaricom's production requirements

What is an MCP Server?

MCP (Model Context Protocol) servers provide capabilities for LLMs to interact with external systems. MCP servers can provide three main types of capabilities:

  • Resources: File-like data that can be read by clients (like API responses)
  • Tools: Functions that can be called by the LLM (with user approval)
  • Prompts: Pre-written templates that help users accomplish specific tasks

Daraja MCP specifically leverages this architecture to connect AI systems with Safaricom's Daraja M-Pesa API.

Overview

Daraja MCP is a bridge between AI, fintech, and M-Pesa, making AI-driven financial automation accessible and efficient. By standardizing the connection between LLMs (Large Language Models) and financial transactions, Daraja MCP allows AI-driven applications to process payments, retrieve transaction data, and automate financial workflows effortlessly.

Key Capabilities

  • AI-Powered M-Pesa Transactions – Enable LLMs to handle B2C, C2B, and B2B payments
  • Standardized Integration – MCP ensures compatibility with multiple AI tools
  • Secure & Scalable – Implements OAuth authentication and supports enterprise-grade transaction handling
  • Flexible Automation – AI agents can query account balances, generate invoices, and automate reconciliation

Requirements

  • Python 3.12
  • Safaricom Daraja API Credentials (Consumer Key and Secret)

Installation

Step 1: Setting Up Your Environment

1. Install uv Package Manager

For Mac/Linux:

bash
curl -LsSf https://astral.sh/uv/install.sh | sh

For Windows (PowerShell):

powershell
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

2. Clone the Repository

bash
git clone https://github.com/jameskanyiri/DarajaMCP.git
   cd DarajaMCP

3. Create and Activate a Virtual Environment

bash
uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

✅ Expected Output: Your terminal prompt should change, indicating the virtual environment is activated.

4. Install Dependencies

bash
uv sync

Step 2: Setting up Environment Variables

1. Copy the example environment file:

bash
cp .env.example .env

2. Update the `.env` file with your actual credentials and configuration values.

> Note: For development, use the sandbox environment. Switch to the production URL when ready.

Usage

Testing with Claude Desktop

1. Install Claude Desktop

    2. Configure Claude Desktop

      bash
      # On MacOS/Linux
           code ~/Library/Application\ Support/Claude/claude_desktop_config.json
      
           # On Windows
           code %APPDATA%\Claude\claude_desktop_config.json

        3. Add Server Configuration

        Choose one of the following configurations:

        #### Anthropic's Recommended Format

        json
        {
             "mcpServers": {
               "daraja": {
                 "command": "uv",
                 "args": [
                   "--directory",
                   "/ABSOLUTE/PATH/TO/PARENT/FOLDER/DarajaMCP",
                   "run",
                   "main.py"
                 ]
               }
             }
           }

        #### Working Configuration (Tested)

        json
        {
             "mcpServers": {
               "DarajaMCP": {
                 "command": "/ABSOLUTE/PATH/TO/PARENT/.local/bin/uv",
                 "args": [
                   "--directory",
                   "/ABSOLUTE/PATH/TO/PARENT/FOLDER/DarajaMCP",
                   "run",
                   "main.py"
                 ]
               }
             }
           }

        > Note:

        >

        > - Replace `/ABSOLUTE/PATH/TO/PARENT` with your actual path

        > - To find the full path to `uv`, run:

        bash
        # On MacOS/Linux
           which uv
        
           # On Windows
           where uv

        4. Verify Configuration

          Tools and Prompts

          Payment Tools

          stk_push

          Initiate an M-Pesa STK push request to prompt the customer to authorize a payment on their mobile device.

          Inputs:

          • `amount` (int): The amount to be paid
          • `phone_number` (int): The phone number of the customer

          Returns: JSON formatted M-PESA API response

          generate_qr_code

          Generate a QR code for a payment request that customers can scan to make payments.

          Inputs:

          • `merchant_name` (str): Name of the company/M-Pesa Merchant Name
          • `transaction_reference_no` (str): Transaction reference number
          • `amount` (int): The total amount for the sale/transaction
          • `transaction_type` (Literal["BG", "WA", "PB", "SM", "SB"]): Transaction type
          • `credit_party_identifier` (str): Credit Party Identifier (Mobile Number, Business Number, Agent Till, Paybill, or Merchant Buy Goods)

          Returns: JSON formatted M-PESA API response containing the QR code data

          Payment Prompts

          stk_push_prompt

          Generate a prompt for initiating an M-Pesa STK push payment request.

          Inputs:

          • `phone_number` (str): The phone number of the customer
          • `amount` (int): The amount to be paid
          • `purpose` (str): The purpose of the payment

          Returns: Formatted prompt string for STK push request

          generate_qr_code_prompt

          Generate a prompt for creating an M-Pesa QR code payment request.

          Inputs:

          • `merchant_name` (str): Name of the merchant/business
          • `amount` (int): Amount to be paid
          • `transaction_type` (str): Type of transaction (BG for Buy Goods, WA for Wallet, PB for Paybill, SM for Send Money, SB for Send to Business)
          • `identifier` (str): The recipient identifier (till number, paybill, phone number)
          • `reference` (str, optional): Transaction reference number. If not provided, a default will be used.

          Returns: Formatted prompt string for QR code generation

          Document Processing Tools

          create_source

          Create a connector from data source to unstructured server for processing.

          Inputs:

          • `connector_name` (str): The name of the source connector to create

          Returns: Source connector details including name and ID

          create_destination

          Create a connector from unstructured server to destination for data storage.

          Inputs:

          • `connector_name` (str): The name of the destination connector to create

          Returns: Destination connector details including name and ID

          create_workflow

          Create a workflow to process data from source connector to destination connector.

          Inputs:

          • `workflow_name` (str): The name of the workflow to create
          • `source_id` (str): The ID of the source connector
          • `destination_id` (str): The ID of the destination connector

          Returns: Workflow details including name, ID, status, type, sources, destinations, and schedule

          run_workflow

          Execute a workflow.

          Inputs:

          • `workflow_id` (str): The ID of the workflow to run

          Returns: Workflow execution status

          get_workflow_details

          Get detailed information about a workflow.

          Inputs:

          • `workflow_id` (str): The ID of the workflow to get details

          Returns: Workflow details including name, ID, and status

          fetch_documents

          Fetch documents analyzed during workflow execution.

          Inputs: None

          Returns: List of analyzed documents

          Prompts

          create_and_run_workflow_prompt

          Generate a prompt to create and run a workflow for document processing.

          Inputs:

          • `user_input` (str): The user's processing requirements

          Returns: Formatted prompt for workflow creation and execution

          Example:

          python
          # Example usage
          prompt = await create_and_run_workflow_prompt(
              user_input="Process all PDF invoices from the invoices folder and store them in the processed folder"
          )
          # Returns: "The user wants to achieve Process all PDF invoices from the invoices folder and store them in the processed folder. Assist them by creating a source connector and a destination connector, then setting up the workflow and executing it."

          Resources

          Currently, no resources are available.

          License

          MIT License

          Acknowledgments

          • Safaricom for providing the Daraja API
          • Anthropic for the MCP framework
          • Contributors to the project

          Contact

          For any inquiries, please open an issue on the GitHub repository.

          Frequently asked questions

          What is DarajaMCP?

          DarajaMCP is a Model Context Protocol (MCP) server listed in the TrackMCP directory.

          How do I install DarajaMCP?

          Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

          Is DarajaMCP open source?

          Yes — it is hosted on GitHub at https://github.com/jameskanyiri/darajamcp and has 14 stars.

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