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Tag: Mcp

  • A2A (Agent-to-Agent) vs. MCP (Model Context Protocol)

    A2A (Agent-to-Agent) vs. MCP (Model Context Protocol) A2A (Agent-to-Agent) vs. MCP (Model Context Protocol) Here’s a comparison between A2A (Agent-to-Agent Protocol) and MCP (Model Context Protocol) in the context of AI agents: A2A (Agent-to-Agent Protocol): Primary Focus: Standardizing communication and interoperability between different AI agents, regardless of their origin or framework. Aims to give AI… Read more

  • Model Context Protocol (MCP) Interfaces

    Model Context Protocol (MCP) Interfaces The acronym “MCP” in the context of interfaces most likely refers to the Model Context Protocol. This open protocol is designed to standardize how AI applications, especially Large Language Models (LLMs), can interact with external data sources and tools in a consistent and interoperable manner. What is the Model Context… Read more

  • Security Issues in LangChain and MCP Servers

    Security Issues in LangChain and MCP Servers Security Issues in LangChain Prompt Injection: Maliciously crafted prompts can manipulate the LLM to perform unintended actions, bypass filters, or disclose sensitive information. This is a primary concern as user input directly influences the LLM’s behavior. Example: A user might craft a prompt like “Ignore previous instructions and… Read more

  • Various MCP Servers and Cloud Availability

    Companies Developing MCP Servers and Cloud Availability A growing number of companies are actively developing and deploying MCP (Model Context Protocol) servers to integrate their services with AI agents. Many of these servers are designed to run in or interact with cloud environments. Companies with Developed MCP Servers (Examples) Technology Platforms Cloudflare: Provides infrastructure for… Read more

  • Exploring LangChain MCP Features with Sample Code

    Exploring LangChain MCP Features with Sample Code LangChain provides integration with the Model Context Protocol (MCP), allowing LLM agents to interact with external tools and data sources managed by an MCP server. This enables powerful capabilities like real-time information retrieval and action execution. Here’s an exploration of key LangChain MCP features with illustrative Python code… Read more

  • Retrieval-Augmented Generation (RAG) Enhanced by Model Context Protocol (MCP)

    RAG Enhanced by MCP: Detailed Explanation The integration of Retrieval-Augmented Generation (RAG) with the Model Context Protocol (MCP) offers a powerful paradigm for building more intelligent and versatile Large Language Model (LLM) applications. MCP provides a structured way for LLMs to interact with external tools and data sources, which can significantly enhance the retrieval capabilities… Read more

  • Model Context Protocol (MCP) for Agentic AI

    The Model Context Protocol (MCP), primarily developed by Anthropic, is an open protocol designed to standardize how applications provide context (data and tools) to large language models (LLMs), which often serve as the foundation for agentic AI systems. It aims to create a universal and efficient way for AI models to interact with various external… Read more