Using MCP AI Agent

What is MCP?

MCP servers can act as a lightweight, static AI agent that browses the web to fetch the latest information on open-source LMs — without requiring full model inference.

Since they’re static, they’re not meant to generate responses — just gather, cache, and serve info — making them ideal for non-interactive use cases.

Perfect for supporting internal teams, developers, or users who need real-time context on open-source models.

Think of them as a “browser + knowledge updater” — not a chatbot, not a model — just a tool that keeps you informed.

Model Context Protocol is an open standard that lets apps talk to external tools in a structured, secure way.

Think of it as a universal adapter: it allows AI models to access local tools, APIs, databases, search engines, or custom scripts through a consistent protocol. Instead of every app inventing its own plugin format, MCP creates one shared language.

Key points:

• It runs servers that expose “tools” such as search, file access, or custom functions.
• LLMs like ChatGPT or LM Studio, AnythingLLM, ollama connect to these servers and call the tools.
• It works locally or over a network and gives you control over permissions.
• Developers can build their own MCP servers to integrate anything from Google Search to Python scripts.

It is designed to make AI setups modular, customizable, and more powerful.

An MCP AI agent refers to an AI agent that uses the Model Context Protocol (MCP) to communicate with external tools and data sources, making it more capable and versatile. MCP is an open standard that acts as a standardized interface, enabling AI agents to securely access and interact with APIs, databases, and applications by providing a common language for calling tools and getting data.

With MCP, you can do web enquiries in a locally run LLM system.

But….I can use Google if i want to run a live search, right? So whats the benefit?

1. Search & Live Data becomes part of your workflow
Instead of switching tabs to Google Chrome and manually searching, the local model can query Google inside your prompt, retrieve results, filter them, summarise them, compare them, cross check them, or turn them into structured data.

2. Fully automated research
You can run a single prompt like
“Find the top 10 Singapore hotels near Marina Bay with prices, sort by rating, and summarise the pros and cons.”
(although these can be done with OpenAI Atlas and Perplexity Comet now, Nov 2025)

The MCP server calls Google search APIs, fetches data, and the model processes everything for you in one chain.

3. Local control and privacy
You stay inside your locally run LLM, not a cloud browser. The model uses your API keys, your rules, your local environment.

Summary

AI Applications – Operate multiple large language models offline to access advanced AI capabilities without internet dependence or subscription platforms. All processing stays on your local network, giving you full control over data privacy and security.

SMB grade LLM – Suitable for Small and Medium Businesses with limited resources, fewer staff, and lower IT infrastructure investment. Cost-efficiency, ease of use, and quick AI deployment, On-premise language models, Data sovereignty.

Retrieval-Augmented Generation Feature – Let AI access your knowledgebase so it can search your documents, PDFs, and images instantly, delivering answers powered by your own data. AI assistants that can answer employee questions using company-specific guides, FAQs, and internal reports. Providing accurate information from internal documentation to answer internal questions about a specific product or policy.

AI Chatbots – Useful for internal teams, offering 24/7 access to Knowledgebase Documentation, FAQs, or task assistance without human intervention.
AI website chatbots can streamline customer support by handling routine queries, reducing wait times, and freeing human agents for complex issues.

Model Context Protocol Feature – MCP enables AI applications, including agents and large language models, to interface directly with external data systems such as browsers. It gives the AI structured access to real time information, research summarization and business intelligence, allowing it to operate with current, context rich data rather than static knowledge.

AI Image & Video Generator – Create unlimited images from text descriptions using deep learning models, which have been trained on vast datasets of existing images and their associated text, giving you fast generation speeds, full privacy, and creative freedom without relying on cloud based services.

ComfyUI  – Powerful open sourced app for building custom workflows such as Outpaint (extending an image), Inpaint (Modify inside an image), Text 2 Image, Reference Image 2 Image, Image to Video, Flux Dev Workflows, Qwen Multi Angle, Relight Scene, Blend, Wan Animate.

Contact MT Research Labs if you’ll like us to incorporate and systemize a local LLM for your enterprise.