Obot Learning Center – Page 2
MCP vs. A2A: Examples, Key Differences, and How to Choose
This is part of a series of articles about Model Context Protocol. Introducing MCP and A2A MCP (Model Context Protocol) and A2A (Agent-to-Agent Protocol) are both AI agent protocols that are considered complementary to each other. MCP focuses on an agent’s interaction with tools, while A2A focuses on collaboration between multiple agents. MCP allows an […]
Top 5 MCP Catalogs in 2026 and Using Them Effectively
This is part of a series of articles about Model Context Protocol. What Is an MCP Catalog? An MCP catalog is a directory of MCP servers that follow the model context protocol. It lists servers by function, capabilities, and supported operations, so a client can connect to them without manual setup. An MCP catalog usually […]
Model Context Protocol: Principles, Use Cases, and Key Technologies
What Is Model Context Protocol (MCP)? Model Context Protocol (MCP) by Anthropic is an open specification proposed by Anthropic, which enables AI models, agents, and supporting infrastructure to share and manage context. MCP defines a set of message formats and APIs that formalize how context, which can include state, instructions, or data, is communicated between […]
9 Amazing Model Context Protocol Use Cases in 2026
This is part of a series of articles about Model Context Protocol. What Are Common Uses Cases of Model Context Protocol (MCP)? Model Context Protocol (MCP) is an open interoperability standard for clear, structured communication between AI models, applications, and tools. It offers conventions and specifications for consistent management and exchange of contextual information across […]
MCP Architecture: Components, Lifecycle, and Client-Server Tutorial
What Is Model Context Protocol Architecture? The model context protocol (MCP) architecture defines a structured way to extend the capabilities of large language models (LLMs) beyond their training data. It introduces a standardized communication layer that allows LLMs to interact with external tools, systems, and data sources. MCP architecture enables dynamic and distributed integration of […]
Defining and Implementing MCP Tools: a Practical Guide
What Are Model Context Protocol (MCP) Tools? This is part of a series of articles about Model Context Protocol. MCP tools are functions exposed by a Model Context Protocol (MCP) server that allow AI models (like Large Language Models) to interact with external systems, perform actions, and access data. These tools enable AI agents to […]
Building with MCP: Anthropic Guidance and Code Execution in Claude
What Is the Model Context Protocol (MCP) by Anthropic? This is part of a series of articles about the Model Context Protocol. The model context protocol (MCP) is a framework introduced by Anthropic for its language models, such as Claude. MCP improves dynamic tool use by enabling language models to interact with code execution environments […]
MCP Gateway: How It Works, Capabilities and Use Cases
What Is a Model Context Protocol Gateway? A Model Context Protocol (MCP) gateway is an intermediary layer that simplifies how AI applications connect to multiple MCP servers. It acts as a single point of entry for AI agents like Claude or ChatGPT to access external tools, resources, and workflows through the MCP protocol. Instead of […]
How MCP Servers Work, Use Cases and Notable Examples
What Is an MCP Server? This is part of a series of articles about Model Context Protocol. MCP servers are applications that expose AI agents to tools and services through the standardized Model Context Protocol (MCP), acting as a bridge between AI models and external data or functionality. They allow AI models to use tools […]
AI Agent Frameworks: Components & Top 5 Open Source Solutions
What Are AI Agent Frameworks? AI agent frameworks are software libraries or platforms that support the development, deployment, and management of intelligent agents. These agents can autonomously perceive their environment, make decisions, and perform tasks to achieve specific goals, often powered by machine learning, deep learning, or rule-based approaches. Frameworks provide reusable tools and standardized […]
Anthropic Claude API: A Practical Guide
Dive into the Claude API – learn to integrate Anthropic’s Claude models into your apps: discover how Claude and Obot can help you build agents, handle prompts, and scale real-world workflows.
AI Copilots: Enterprise Use Cases and Key Considerations
AI copilots are digital assistants using AI, often large language models (LLMs), to help with tasks like code generation, creative writing, and decision making.