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“We built CustomGPT.ai so businesses could get real value from AI, faster and without technical expertise.”
Trae can call an external MCP server, so its agents answer from your own documents rather than from general model knowledge. A hosted MCP server means there is nothing to run yourself: you add the server to Trae’s MCP configuration, point it at your knowledge base, and the agents retrieve from it. Using Trae is […]
Introduction To connect an AI tool to a CustomGPT.ai hosted MCP server, open your CustomGPT.ai project, copy your Project ID and MCP token, then add the hosted MCP server URL or JSON configuration to your AI tool’s MCP settings. The URL follows this format: https://mcp.customgpt.ai/projects/<PROJECT_ID>/sse?token=<TOKEN>. After saving and restarting the tool, you can ask questions […]
MCP AMA recording LINK – https://www.youtube.com/watch?v=hZWPAuBzmVs Our recent MCP AMA brought together a stellar panel of experts from across the AI ecosystem—spanning academia, major tech players, infrastructure providers, and applied AI startups. Moderated by Bill Cava (CEO of Generative Labs and adviser to CustomGPT.ai), the conversation featured: The discussion was a deep dive into the […]
The AI landscape is crowded with platforms claiming to offer platform integrations. But when you look closer, as many startup teams do, there’s a fundamental difference in what these platforms actually let you do. While most stop at internal tools for your team, CustomGPT.ai goes further – enabling you to deploy action-capable agents directly to […]
Quick Answers Your AI agent answers questions perfectly… but your customers want more. They want their meeting booked. Their order tracked. Their ticket created. Right now. In the same conversation. Every “I’ll do that for you” that becomes “Please do this yourself” costs you a customer. Why Your Current AI Agent Feels Like Half a […]
In the evolving landscape of AI integrations, the Model Context Protocol (MCP) has emerged as a pivotal standard for connecting large language models (LLMs) with external data sources and tools. While MCP encompasses both client and server components, this guide zeroes in on the MCP client—its architecture, implementation, advanced features, and practical applications. Whether you’re […]
TL;DR, MCP is the “USB‑C for AI tools.” It defines a universal JSON‑over‑HTTP interface that lets any language model dynamically discover, describe, and invoke external capabilities, without bespoke adapters. In this post we unpack each feature of MCP, share sample configs, and offer writing tips to help you explain MCP clearly and convincingly. 1 Why […]
Quick vibe‑check: If you’re still googling “What is JSON?” this article will hurt your feelings. We’re talking to the folks who bliss‑edit YAML in Vim and dream in HTTP status codes. Ready? Cool, let’s nerd‑out … with a smile. Role of the MCP Server in the Ecosystem An MCP server is the authoritative endpoint that […]
Last month (on 29th May) we hosted a live AMA on the Model Context Protocol (MCP), fielding over 40 insightful questions from engineers, architects, and AI enthusiasts around the world. We couldn’t answer every query in real time, so below is a detailed write-up—organized by theme—with answers from our panelists Santiago, Alden, and Roy. Get […]
You’ve probably noticed that today’s AI models can do amazing things—drafting emails, summarizing documents, even answering complex customer questions. But behind the scenes, they often struggle when it comes to getting up-to-the-minute facts or diving into your company’s own private data. That’s where the Model Control Protocol (MCP) comes in. In a recent online discussion, […]