DEV Community· technonotes-hacker·· 3 小時前AI 評分19
LLM 工具呼叫與 MCP
LLM - Tool Calling & MCP
AI 導讀
LLM 工具呼叫由模型指出要呼叫的工具;MCP 是 AI 工具的通用標準,MCP client 會選擇要呼叫的方法。文中以 LangChain 説明一種工具呼叫方式,並指出自訂工具與 function calling 是相同概念的不同實作方式。資料庫工具在 PROD 僅允許 SELECT;加入人工介入後可使用 update,但在 PROD 更新仍有風險。
正文
Function Calling - The Manual Tool LOOP
- LLM ( ChatGroq ) Will say which tool needs to be called.
- List or the Object will have some value.
- This is with Langchain and one type of Tool Calling.
Custom Tool
- Its a structured way.
External API Tools
- These are the APIs which we are going to call.
Database Tools
- Create a custom table.
- We are allowing only SELECT in PROD.
- But if we use HUMAN in the loop , then update can be also used - But make sure its also RISK to use in PROD to update a query.
- Qwen Models --> Mostly you can use this for local testing.
MCP - Model Context Protocol
- Its a protocol.
- MCP is a common standard (like USB for AI tools).
- MCP client will decide which method to call.
- இப்ப ஒரு API expose பண்ணும்போது அதுல PUT GET எல்லாமே இருக்கும், but இந்த MCPல , APIல எல்லாத்தையும் club பண்ணி , எல்லாத்தையும் expose பண்ணுவாங்க . MCP cleint will take care which one to call like a Agent.
Questions & Things to know
Notes
- Langchain is a Framework.
- Function description --> https://developers.openai.com/api/docs/guides/function-calling?api-mode=responses
- Tool Calling ( description , above one )
- With pydantic we achieved DATA validation --> Return you will get in Object flow.
- Sqlite --> File based DB.
- esh --> english to shell , project --> https://github.com/numericalworks/esh
- ER Model Will be generated from the tool , before LLM become famous.
- Ollama or Llama cpp ?
- Custom Tool or Function calling --> Both are same , there are different methods.
- General Method --> API with swagger , You will get the request and response with PUT GET etc. Now the MCP Client will search and decide , which method to call.
來源:DEV Community · dev.to















