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MCP RAG

by kalicyh

learn_text

Add new text to the knowledge base for future reference and retrieval. Store facts, definitions, notes, or conversation context to enhance search and Q&A capabilities.

Instructions

向 RAG 知识库添加一段新文本以供将来参考。 使用场景:

  • 添加事实、定义或解释

  • 存储对话中的重要信息

  • 保存研究发现或笔记

  • 添加特定主题的上下文

参数: text: 要学习并存储在知识库中的文本内容。 source_name: 来源的描述性名称(例如 "user_notes", "research_paper", "conversation_summary")。

Input Schema

NameRequiredDescriptionDefault
textYes
source_nameNomanual_input

Input Schema (JSON Schema)

{ "properties": { "source_name": { "default": "manual_input", "title": "Source Name", "type": "string" }, "text": { "title": "Text", "type": "string" } }, "required": [ "text" ], "type": "object" }

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kalicyh/mcp-rag'

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