DarajaMCP
A Model Context Protocol server that integrates AI applications with Safaricom's Daraja API, enabling AI-driven financial transactions and automation through M-Pesa services.
A Model Context Protocol server that integrates AI applications with Safaricom's Daraja API, enabling AI-driven financial transactions and automation through M-Pesa services.
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
MCP (Model Context Protocol) servers provide capabilities for LLMs to interact with external systems. MCP servers can provide three main types of capabilities:
Daraja MCP specifically leverages this architecture to connect AI systems with Safaricom's Daraja M-Pesa API.
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.
For Mac/Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
For Windows (PowerShell):
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
git clone https://github.com/jameskanyiri/DarajaMCP.git
cd DarajaMCP
uv venv
source .venv/bin/activate # On Windows: .venvScriptsactivate
✅ Expected Output: Your terminal prompt should change, indicating the virtual environment is activated.
uv sync
cp .env.example .env
.env
file with your actual credentials and configuration values.Note: For development, use the sandbox environment. Switch to the production URL when ready.
Install Claude Desktop
Download and install the latest version from Claude Desktop
Make sure you're running the latest version
Configure Claude Desktop
Open your Claude Desktop configuration file:
# On MacOS/Linux
code ~/Library/Application Support/Claude/claude_desktop_config.json
# On Windows
code %APPDATA%Claudeclaude_desktop_config.json
Create the file if it does not exist
Add Server Configuration Choose one of the following configurations:
#### Anthropic's Recommended Format
{
"mcpServers": {
"daraja": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/DarajaMCP",
"run",
"main.py"
]
}
}
}
#### Working Configuration (Tested)
{
"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:
# On MacOS/Linux
which uv
# On Windows
where uv
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 paidphone_number
(int): The phone number of the customerReturns: JSON formatted M-PESA API response
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 Nametransaction_reference_no
(str): Transaction reference numberamount
(int): The total amount for the sale/transactiontransaction_type
(Literal["BG", "WA", "PB", "SM", "SB"]): Transaction typecredit_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
Generate a prompt for initiating an M-Pesa STK push payment request.
Inputs:
phone_number
(str): The phone number of the customeramount
(int): The amount to be paidpurpose
(str): The purpose of the paymentReturns: Formatted prompt string for STK push request
Generate a prompt for creating an M-Pesa QR code payment request.
Inputs:
merchant_name
(str): Name of the merchant/businessamount
(int): Amount to be paidtransaction_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
Create a connector from data source to unstructured server for processing.
Inputs:
connector_name
(str): The name of the source connector to createReturns: Source connector details including name and ID
Create a connector from unstructured server to destination for data storage.
Inputs:
connector_name
(str): The name of the destination connector to createReturns: Destination connector details including name and ID
Create a workflow to process data from source connector to destination connector.
Inputs:
workflow_name
(str): The name of the workflow to createsource_id
(str): The ID of the source connectordestination_id
(str): The ID of the destination connectorReturns: Workflow details including name, ID, status, type, sources, destinations, and schedule
Execute a workflow.
Inputs:
workflow_id
(str): The ID of the workflow to runReturns: Workflow execution status
Get detailed information about a workflow.
Inputs:
workflow_id
(str): The ID of the workflow to get detailsReturns: Workflow details including name, ID, and status
Fetch documents analyzed during workflow execution.
Inputs: None
Returns: List of analyzed documents
Generate a prompt to create and run a workflow for document processing.
Inputs:
user_input
(str): The user's processing requirementsReturns: Formatted prompt for workflow creation and execution
Example:
# 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."
Currently, no resources are available.
For any inquiries, please open an issue on the GitHub repository.