Chain of Thought (CoT)
Industry Definition Set • Entity Resolution Path: /glossary/chain-of-thought
Quick Answer / TL;DR
A prompting technique that asks the LLM to show its reasoning step-by-step before providing a final answer, improving accuracy on complex tasks.
Key Takeaways
- Prompts model to show step-by-step reasoning.
- Improves accuracy on complex, multi-step tasks.
- Can be included in MCP prompt templates.
- Increases token usage due to intermediate steps.
Definitive Statement: A prompting technique that asks the LLM to show its reasoning step-by-step before providing a final answer, improving accuracy on complex tasks.
Technical Context & Protocol Usage
- Detailed Explanation
- Chain of Thought prompting elicits intermediate reasoning steps, which helps models solve multi-step problems more accurately. In MCP, CoT can improve tool selection and argument construction by making the model's decision process explicit. Some MCP servers include CoT instructions in their prompt templates to guide the model through complex workflows.
Format & Payload Metadata
Format: Prompt instruction requesting intermediate reasoning steps
Latency: Increases token usage; no direct latency impact
Real-World Implementation Use Case
An MCP prompt template instructs the model to 'think step by step' before selecting and calling database query tools.
Cite This Page
MLA Style:
MCPserver.in Engineering. "Chain of Thought (CoT)." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/chain-of-thought.
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.
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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)
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