MCP, LLM connectors, and AI agents connecting to APIs — Claude, ChatGPT, and beyond
Custom MCP servers cost $50K–$150K per integration per year. Learn when to build vs. buy MCP infrastructure, and how managed MCP providers eliminate OAuth and maintenance overhead.
Native LLM connectors only scratch the surface. Learn how managed MCP servers give Claude full access to 100+ SaaS APIs — no custom infrastructure required.
Compare the best MCP servers for Attio CRM in 2026. Open-source vs. Attio's hosted MCP vs. Truto's managed server — with setup guides for Claude, ChatGPT, and custom agents.
Compare the best MCP servers for Fathom in 2026. Connect Fathom meeting transcripts to Claude, ChatGPT, Cursor, and LangChain agents without managing API keys or rate limits.
Compare the top Slack MCP servers for AI agents in 2026: open-source options vs. Truto's managed MCP with full API coverage, managed OAuth, and enterprise security.
Learn how to build scalable, multi-step AI agents using LangGraph and LangChain while solving the hardest part of agentic workflows: SaaS API integration.
Connect ChatGPT directly to 100+ SaaS apps using SuperAI by Truto. Expose raw APIs as LLM tools with strict CRUD access controls, managed pagination, and zero integration code.
A comprehensive guide to MCP security: understand key threats, examples, and effective strategies to secure your AI integrations.
MCP, or Model Context Protocol, gives AI assistants a standard way to use external apps and data safely. This guide explains how hosts, servers, and tools interact, how JSON validation and structured results keep calls reliable, and why Unified APIs make integrations faster and easier to manage.
Truto’s AI-ready integrations make any API accessible to AI agents and MCP servers, so you can build secure, consistent AI features faster and with less effort.
Newest offering of Truto SuperAI. It helps teams using Truto convert the existing integrations endpoints into tools usable by LLM agents.
Truto provides a comprehensive solution that supports every step of your RAG-based workflow. Learn more in this blog post.
