What is Mcp Beckn

MCP-Beckn is a server that acts as a bridge between AI systems and Beckn’s interoperable transaction networks, utilizing the Model Context Protocol (MCP) for communication.

Use cases

Use cases include enabling AI assistants to book services, retrieve information, and execute transactions through the Beckn network, enhancing user experience in service-oriented applications.

How to use

To use MCP-Beckn, clone the repository, install the necessary dependencies, and configure the environment. The server processes requests from AI assistants and interacts with real-world services through the Beckn Protocol.

Key features

Key features include the MCP Server for handling requests, an Intent Mapper for translating natural language to Beckn operations, a Goose Orchestrator for managing workflows, and a Beckn Client for interacting with Beckn networks.

Where to use

MCP-Beckn can be used in various domains where AI assistants need to interact with real-world services, such as e-commerce, transportation, and service delivery.

Beckn-MCP Integration

A bridge between AI systems (via the Model Context Protocol) and Beckn’s interoperable transaction networks.

flowchart TD
    User[User] --> |Natural Language Request| AI[AI Assistant]
    AI --> |MCP Request| MCP[MCP Server]
    
    subgraph "Beckn-MCP Integration"
        MCP --> Intent[Intent Mapper]
        Intent --> |Structured Intent| Goose[Goose Orchestrator]
        Goose --> |Tool Execution| Beckn[Beckn Client]
    end
    
    Beckn --> |Protocol Request| BN[Beckn Network]
    BN --> |Domain Requests| Providers[Service Providers]
    
    Providers --> |Service Response| BN
    BN --> |Protocol Response| Beckn
    Beckn --> |Results| Goose
    Goose --> |Workflow Result| MCP
    MCP --> |MCP Response| AI
    AI --> |Natural Language Response| User
    
    class User,AI,Providers external
    class MCP,Intent,Goose,Beckn primary
    class BN secondary

    classDef external fill:#f9f9f9,stroke:#333,stroke-width:1px
    classDef primary fill:#d8e8f4,stroke:#0066cc,stroke-width:1px
    classDef secondary fill:#e8f4d8,stroke:#339900,stroke-width:1px

Project Overview

This project implements a server that enables AI assistants to interact with real-world services through Beckn Protocol networks. It uses Model Context Protocol (MCP) to receive requests from AI models and supports pluggable orchestration frameworks.

Key Components

• MCP Server: Handles MCP protocol requests from AI systems
• Intent Mapper: Translates natural language intents to Beckn operations
• Orchestration Layer: Manages workflows with pluggable engines (Goose, MindNet, etc.)
• Beckn Client: Interacts with Beckn networks following the protocol

Getting Started

Prerequisites

• Node.js (v18+)
• TypeScript
• Docker (optional, for containerized deployment)

Installation

1. Clone this repository

git clone https://github.com/yourusername/mcp-beckn.git
cd mcp-beckn

2. Install dependencies

npm install

3. Configure environment

cp .env.example .env
# Edit .env with your configuration

4. Start the development server

npm run dev

Architecture

The system follows a modular architecture with clear separation of concerns:

1. AI assistants send requests via MCP
2. Intent mapping transforms natural language to structured intents
3. Pluggable orchestration manages the transaction workflow
4. Beckn client handles protocol-specific operations

For more details, see the Technical Proposal.

Orchestration Engines

The system supports multiple orchestration engines that can be configured via the ORCHESTRATOR_TYPE environment variable:

• Goose (default): Block’s workflow orchestration framework
• MindNet: Memory-persistent, Knowledge Graph-driven orchestration (placeholder)
• LangGraph: LangChain’s graph-based workflow engine (placeholder)
• Custom: Create and plug in your own orchestration engine

To create your own orchestrator:

# Generate boilerplate for a new orchestrator
node scripts/create-orchestrator.js MyOrchestrator

# Configure to use it
echo "ORCHESTRATOR_TYPE=my-orchestrator" >> .env

# Run with your custom orchestrator
npm run dev

See Custom Orchestrators Guide for detailed instructions.

Quick Demo

# Clone and start the project
git clone https://github.com/yourusername/mcp-beckn.git
cd mcp-beckn
npm install
npm run dev

# In another terminal, test with a sample request:
curl -X POST http://localhost:3000/mcp/v1 \
  -H "Content-Type: application/json" \
  -d '{"query": "Book me a cab from MG Road to the airport", "context": {"user_id": "user123"}}'

Development Roadmap

• Phase 1 (Current): Basic MCP server with Beckn search capabilities
• Phase 2 (Q2 2025): Full transaction lifecycle support (search, select, init, confirm)
• Phase 3 (Q3 2025): Multi-domain support and advanced NLU
• Phase 4 (Q4 2025): Production-ready implementation with real Beckn network integration

Contributing

This project is in early development and welcomes contributions. Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Beckn Protocol community
• Anthropic for the Model Context Protocol
• Block for the Goose orchestration framework