Turn Your AI into a Phone-Powered Assistant

Stop building AI assistants that can only chat. The Didlogic MCP Server bridges the gap between conversational AI and real-world telephony, giving your LLMs the power to make calls, manage phone systems, and handle telecommunications like a seasoned telecom engineer.

The Problem with AI-Powered Telephony

Most developers building AI assistants hit the same wall: their brilliant conversational AI can analyze, reason, and respond to complex queries, but the moment you need it to actually do something in the real world—like make a phone call, check call history, or manage SIP accounts—you're back to writing custom integration code.

Telephony APIs are notoriously complex. Even simple tasks like checking account balances or reviewing call logs require understanding provider-specific endpoints, authentication schemes, and data formats. Your AI assistant becomes just another chatbot instead of a true productivity multiplier.

What This Changes

The Didlogic MCP Server transforms your LLM into a telecommunications powerhouse. Through the standardized Model Context Protocol, your AI can:

• Make and manage calls directly through natural language requests
• Monitor account balances and spending across telephony services
• Handle SIP account provisioning without diving into telecom configuration details
• Review call history and analytics to provide insights on communication patterns
• Manage IP restrictions and security policies conversationally
• Track purchases and transactions with full financial oversight

Instead of building separate tools for each telephony task, you get a unified interface that speaks directly to your LLM.

Real-World Impact

Customer Support Automation: Build AI agents that can actually call customers back, not just send emails. Your support bot can initiate three-way calls with specialists, review previous call interactions, and manage callback queues—all through conversational commands.

IT Operations: "Show me all calls from the London office yesterday, then provision three new SIP accounts for the new hires." Your AI operations assistant handles both the analysis and the provisioning without switching contexts.

Sales Intelligence: Your AI can analyze call patterns, identify high-value prospects based on call duration and frequency, then automatically set up follow-up calls with the right team members.

Financial Oversight: Instead of logging into multiple dashboards, ask your AI: "What's our monthly telephony spend trending toward, and which accounts are driving the highest costs?" Get instant answers with the context to take action.

Implementation That Actually Works

The server integrates seamlessly with your existing LLM setup. Add it to Claude with a simple JSON configuration:

"mcpServers": {
  "didlogic": {
    "command": "uvx",
    "args": ["didlogic_mcp"],
    "env": {
      "DIDLOGIC_API_KEY": "YOUR_API_KEY"
    }
  }
}

No complex webhook setups, no middleware to maintain. Your AI immediately gains access to the full Didlogic API through natural language—everything from balance checks to call initiation becomes conversational.

The server handles authentication, rate limiting, and error handling behind the scenes. Your focus stays on building AI workflows, not debugging telephony integrations.

Beyond Basic Automation

This isn't just about automating existing telephony tasks—it's about creating entirely new possibilities. When your AI can seamlessly move between analyzing conversation transcripts, checking account metrics, and initiating new calls based on that analysis, you're building genuinely intelligent communication systems.

Your AI can correlate call patterns with business outcomes, automatically adjust SIP configurations based on usage patterns, and provide proactive insights about communication infrastructure—all through the same conversational interface your users already understand.

Ready to give your AI real-world telephony superpowers? The Didlogic MCP Server makes it possible with a single pip install.