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aicastle-school-openai-api-agent-project

aicastle-school-openai-api-agent-project

Remote
github.com/aicastle-schoolFinance11Updated 54w ago
Repository

About aicastle-school-openai-api-agent-project

OpenAI Agent School is course material from AI Castle on building AI agents with OpenAI. The README lists ebook and branch links, but gives no stock-price server details.

Key features

  1. 01OpenAI agent course material
  2. 02Ebook link
  3. 03Render Chat branch link
  4. 04Smithery Stock Price branch link
  5. 05Fine Tuning branch link

Use cases

  1. 01Study building AI agents with OpenAI
  2. 02Explore the listed course branches

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://server.smithery.ai/@aicastle-school/openai-api-agent-project/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://server.smithery.ai/@aicastle-school/openai-api-agent-project/mcpAuth required

Tools

Details

From the project README

OpenAI Agent School

(주)에이아이캐슬에서 만든 OpenAI Agent School (OpenAI를 활용한 나만의 AI 에이전트 만들기) 강의 자료입니다.

OpenAI Agent School (Ebook) 바로가기
Render Chat (Branch) 바로가기
Smithery Stock Price (Branch) 바로가기
Fine Tuning (Branch) 바로가기

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.