Large Language Model (LLM)
Industry Definition Set • Entity Resolution Path: /glossary/large-language-model
Quick Answer / TL;DR
A deep neural network trained on massive text corpora to predict and generate human-like text, forming the intelligence core of modern AI agents and MCP-connected systems.
Key Takeaways
- Transformer-based models trained on massive text corpora.
- Power reasoning, planning, and tool selection in AI agents.
- Context window limits how much text can be considered at once.
- Quality varies significantly by model size, training data, and alignment.
Definitive Statement: A deep neural network trained on massive text corpora to predict and generate human-like text, forming the intelligence core of modern AI agents and MCP-connected systems.
Technical Context & Protocol Usage
- Detailed Explanation
- Large Language Models are transformer-based architectures with billions of parameters trained on trillions of tokens. They power the reasoning, planning, and language understanding capabilities of AI agents. In MCP contexts, LLMs serve as the 'brain' that decides which tools to call, interprets tool results, and generates user-facing responses. Popular models include GPT-4, Claude, Gemini, and Llama.
Format & Payload Metadata
Format: Model weights (various formats: GPTQ, GGUF, safetensors)
Latency: First-token latency: 200ms-2s depending on model and hardware
Real-World Implementation Use Case
A Claude model analyzes a user's request and decides to call a `database_query` MCP tool to fetch data before composing an answer.
Cite This Page
MLA Style:
MCPserver.in Engineering. "Large Language Model (LLM)." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/large-language-model.
Related Terms
Model Context Protocol (MCP)
An open, secure protocol that standardizes how artificial intelligence agents and large language models (LLMs) exchange context, tools, prompts, and data resources with external servers.
JSON-RPC 2.0
A lightweight, stateless remote procedure call (RPC) protocol defined in JSON that utilizes request, response, and notification message frames.
Stdio Transport (Standard Input/Output)
A local-only transport mechanism where the AI client spawns the MCP server as a child process and communicates via standard input (stdin) and standard output (stdout) channels.
SSE Transport (Server-Sent Events)
A lightweight, unidirectional HTTP-based streaming protocol used by remote MCP servers to push messages to AI clients, with client-to-server writes sent over standard POST requests.
Deploy Secure MCP Clusters
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