Content
# 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](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**
- Download and install the latest version from [Claude Desktop](https://claude.ai/desktop)
- Make sure you're running the latest version
2. **Configure Claude Desktop**
- Open your Claude Desktop configuration file:
```bash
# On MacOS/Linux
code ~/Library/Application\ Support/Claude/claude_desktop_config.json
# On Windows
code %APPDATA%\Claude\claude_desktop_config.json
```
- Create the file if it doesn't exist
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**
- Save the configuration file
- Restart Claude Desktop
- Look for the hammer 🔨 icon in the interface
- Click it to see the available tools:
- generate_access_token
- stk_push (Future Implementation)
- query_transaction_status (Future Implementation)
- b2c_payment (Future Implementation)
- account_balance (Future Implementation)
## 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](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.
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