Model-Context-Protocol -

This MCP server setup demonstrates a local weather MCP service and a Stripe API MCP bridge. The local-weather server exposes a weather-fetching tool that your MCP host can call to retrieve current weather data for a given city. The stripe-api server provides a unified MCP endpoint to interact with Stripe-like capabilities (e.g., payment intents, customer data) through the MCP protocol. Use the MCP client tooling to discover available tools, initialize connections, and then invoke the desired tool calls, receiving structured results that can be integrated into your AI workflows. The environment is designed to minimize bespoke integration logic by leveraging the standardized JSON-RPC primitives and the MCP tool discovery flow.

Prerequisites

• Node.js (recommended LTS) and npm installed on your system
• Basic familiarity with JSON-RPC and MCP concepts

1. Prepare your environment

• Install Node.js from https://nodejs.org
• Ensure npm is up to date: npm install -g npm

2. Clone or download the MCP server repository (or use your existing project that implements MCP servers)

• git clone https://github.com/hemakumar0077-model-context-protocol-mcp-/repo-name
• cd repo-name

3. Install dependencies

• npm install

4. Run individual MCP servers

• For the local weather server:
  • Ensure weather-server.js exists at the specified path (/path/to/weather-server.js)
  • Start: node /path/to/weather-server.js
• For the Stripe-like MCP bridge:
  • Ensure any required environment/config is provided (e.g., API keys)
  • Start: node path/to/stripe-mcp-bridge.js (adjust as per your project)

5. Register MCP servers with the client config

• Create or edit mcp.json (or your preferred config) to include: { "mcpServers": { "local-weather": { "command": "node", "args": ["/path/to/weather-server.js"] }, "stripe-api": { "url": "https://mcp.stripe.com", "auth": { "type": "bearer", "token": "your-api-key" } } } }

6. Run the MCP host/client that loads the configuration

• Example (in code): load mcp.json and initialize connections to the servers
• Alternatively, run any provided inspector or SDK tooling to test tool discovery and calls

Tips and caveats:

• Ensure the command paths and URLs in mcp.json are accessible from the host environment.
• For services that require authentication (e.g., Stripe-like bridge), securely manage API keys and avoid hard-coding secrets in code or config files.
• Use the MCP Inspector or similar debugging tools to verify tool discovery and call flows before integrating into user-facing AI workflows.
• If a server goes offline, implement a graceful retry strategy and proper error handling in the MCP client to avoid cascading failures in your host application.