Mcpholder MCP Client

Mcpholder – An MCP‑Ready Mobile Client for AI Models

Mcpholder is a lightweight, cross‑platform client built with Flutter that brings the full power of the Model Context Protocol (MCP) to mobile devices. By acting as a local MCP server, it aggregates external Cloudflare‑hosted services and exposes them to AI models such as Claude‑3 Sonnet 3.7. This solves the problem of running complex, tool‑enabled AI workflows on a phone or tablet without needing a dedicated backend. Developers can now prototype, test, and iterate on tool‑based interactions directly from their mobile device.

The core of Mcpholder is its MCP service dashboard. Users can view all available MCP endpoints, add new ones by specifying a name, URL, and optional port, and test connectivity in real time. Once registered, the client performs OAuth authentication to obtain a unique client ID and token, then discovers the tools exposed by the remote MCP. These tools are automatically listed in a local repository and become callable from any AI conversation session. The AI chat page lets developers pick a model (defaulting to Claude‑3 Sonnet) and send natural language prompts. When the prompt requires external data or actions, the underlying AI model triggers the appropriate MCP tool, and the client streams the result back to the chat interface.

Key capabilities include:

• Tool discovery and registration – automatically pulls tool definitions from any MCP‑compatible service.
• OAuth flow integration – handles secure authentication and token management for protected services.
• Live testing console – allows developers to validate new MCP endpoints before adding them to the production list.
• Cross‑platform Flutter UI – offers a consistent experience on iOS, Android, and desktop.

Real‑world scenarios that benefit from Mcpholder are abundant. A mobile developer can quickly build a “calculator” MCP service on Cloudflare, register it with the app, and then ask Claude to solve arithmetic problems directly from a phone conversation. In a more advanced use case, the same workflow could be extended to fetch weather data, query a database, or trigger an IoT device—all while keeping the entire interaction local to the mobile client.

Because Mcpholder runs natively on the device, it eliminates latency introduced by external API gateways and provides a sandboxed environment for experimenting with new MCP services. Its tight integration with the OpenRouter API and support for future model upgrades make it a versatile tool in any AI‑powered development pipeline.