Large Language Models (LLMs) MCP Server
@RahulSaini02
基本信息
关于 Large Language Models (LLMs) MCP Server
This repo is dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.
Large Language Models (LLMs) MCP Server 配置
Large Language Models (LLMs) MCP Server 工具
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is 🤖 Large Language Models (LLMs)?
This repository is a learning resource dedicated to large language models, prompt engineering, and modern generative AI tools such as LangChain, RAG, and vector databases.
How to use 🤖 Large Language Models (LLMs)?
Browse the folder structure to access learning materials on transformer architecture, prompt engineering strategies, and LangChain/RAG pipelines. No installation or configuration steps are described.
Key features of 🤖 Large Language Models (LLMs)?
- Transformer architecture, pretraining vs finetuning, and Hugging Face models
- Prompting strategies, few-shot prompting, and instruction tuning
- LangChain pipelines, RAG systems, memory, tools, and vector databases
Use cases of 🤖 Large Language Models (LLMs)?
- Learning the fundamentals of transformer models and fine-tuning
- Mastering prompt engineering techniques for various tasks
- Building retrieval-augmented generation (RAG) systems with Lang
记忆与知识 分类下的更多 MCP 服务器

Semantic Ui React
Semantic-OrgThe official Semantic-UI-React integration

Scento Perfume API (MCP server): free fragrance API, no key
ScentoScento Perfume API is a free fragrance API and perfume notes database for developers and AI agents. Search 1,500+ perfumes and 400+ ingredients, compare scents, find similar perfumes, map scent families and build occasio

Memory
modelcontextprotocolModel Context Protocol Servers

Stele
Stele-DevShared memory for AI coding agents. Claude Code, Cursor and Codex read your project's decisions, lessons and tasks before they act.

PLUR
plur-aiAI agents start every session with amnesia — you re-explain the project, repeat your preferences, and correct the same mistakes over and over. PLUR gives them a memory that persists. Your agent's corrections, preference
评论