Didlogic MCP Server

Overview

The Didlogic MCP Server provides a standardized, Model Context Protocol (MCP) interface for interacting with the Didlogic API. It enables large language models and AI assistants to perform a full range of telecommunication operations—such as managing SIP accounts, handling balance and transaction histories, controlling IP restrictions, and processing purchases—directly from within their conversational context. By exposing these services as MCP tools and prompts, the server eliminates the need for developers to write custom API wrappers or handle authentication logic manually.

This MCP implementation is valuable for teams building AI‑powered telecom solutions. It abstracts the intricacies of Didlogic’s REST endpoints into a simple, declarative toolset that can be invoked by the model in natural language. For example, a user could ask the assistant to “add a new SIP friend with number +15551234567” and the model will translate that request into the appropriate API call, handling authentication with a bearer token automatically. This seamless integration speeds up prototyping and reduces the risk of security misconfigurations.

Key features include:

• Full API coverage – Every major Didlogic endpoint is exposed as an MCP tool, from balance checks to call history retrieval.
• Specialized prompts – Pre‑built prompt templates streamline common tasks, allowing the model to generate correct request payloads with minimal user input.
• Multi‑transport support – The server can run in STDIO (for local desktop assistants), HTTP, or SSE modes, giving developers flexibility to choose the most suitable communication channel.
• Environment‑driven configuration – API keys and base URLs are supplied via environment variables, keeping secrets out of code and simplifying deployment.

Real‑world scenarios where this server shines include:

• AI‑driven customer support – Agents can query call logs or adjust SIP settings on the fly without leaving the chat interface.
• Telecom automation – Scripts or workflow orchestrators can invoke balance top‑ups, purchase plans, or IP restriction updates triggered by model decisions.
• Rapid prototyping – Start‑up teams can prototype new voice or messaging features in a conversational IDE, leveraging the MCP tools without writing boilerplate HTTP clients.

Integrating the Didlogic MCP into an AI workflow is straightforward: configure the assistant (Claude, Claude Code, or any MCP‑compatible client) to point at the server’s command or URL, provide the API key as an environment variable or bearer token, and begin issuing high‑level commands. The server translates these into precise API calls, returns structured responses, and even streams updates via SSE for real‑time monitoring. This tight coupling of natural language intent with telecommunication infrastructure makes the Didlogic MCP Server a powerful asset for developers looking to embed robust voice and messaging capabilities into AI applications.