Tip.md x402+CDP MCP Server

Overview

The MCP Server collection provides a unified, protocol‑driven interface for common data services that AI assistants need to enrich their responses. By exposing stock market information, image‑to‑text conversion, and a ByteDance API wrapper through the Model Context Protocol, it removes the friction of integrating disparate third‑party services into a single AI workflow. Developers can point their Claude or other MCP‑compatible assistants at these endpoints and instantly add real‑time market data, visual understanding, or social media insights without writing custom adapters.

What Problem It Solves

Modern AI applications often require up‑to‑date external data—financial quotes, image captions, or platform analytics—to provide contextually relevant answers. Without a standardized interface, each data source demands its own SDK, authentication flow, and error handling logic. The MCP Server solves this by normalizing those interactions into a single protocol: every service exposes the same request/response contract, allowing an AI assistant to query any of them with a single, consistent command. This dramatically reduces boilerplate code and speeds up feature rollout.

Core Functionality

• Stock Market Service – Listens on port 8124 and returns Chinese equity data such as current prices, historical trends, and market indices. The service can be queried via a simple JSON payload that specifies the ticker symbol and desired data fields.
• Image‑to‑Text Service – Accepts an image (or URL) and returns a textual description or extracted text, enabling visual content to be processed by language models without external OCR services.
• ByteDance API Wrapper – Provides a thin abstraction over ByteDance’s platform APIs, handling authentication tokens and rate limits internally so that assistants can retrieve posts, comments, or analytics effortlessly.

Each service is packaged as a lightweight Python script that can be started with minimal configuration, and the README shows how to launch them from a command line or integrate them into Claude Desktop’s configuration file.

Use Cases and Scenarios

• Financial Chatbots – A virtual assistant can answer “What is the latest price of 600519?” by querying the stock service, then compose a contextual report that includes recent earnings data and market sentiment from ByteDance.
• Content Moderation – An image uploaded by a user is sent to the image‑to‑text service, and the resulting caption is fed back into a policy model that flags inappropriate material before it reaches end users.
• Social Media Analytics – A marketing tool can pull trending posts from ByteDance, enrich them with sentiment scores, and cross‑reference stock performance to assess brand impact in real time.

Integration into AI Workflows

Developers add the MCP servers to their local or cloud environment and reference them in the AI client’s configuration (e.g., Claude Desktop’s ). The assistant then issues a standard MCP command, receives the JSON response, and can directly embed that data into its output or trigger downstream processing. Because all services adhere to the same protocol, a single wrapper library can handle routing, retry logic, and error translation for any of the endpoints.

Unique Advantages

• Protocol Uniformity – A single MCP contract across multiple domains eliminates the need for custom adapters.
• Zero‑Dependency Deployment – The services run as simple scripts with no external service orchestration required.
• Extensibility – New data providers can be added by following the same folder structure and MCP contract, making the ecosystem grow organically.

In summary, the MCP Server collection empowers developers to seamlessly fuse real‑time data into AI assistants, enabling richer, contextually aware interactions across finance, vision, and social media domains.