I recently built a system where an LLM agent posts messages to Slack via a remote MCP (Managed Control Plane) server using LangChain. At first, I let an AI code generation model write the integration code. While the AI generated code fast, getting it to actually work reliably took several frustrating iterations.

Key challenges included:

    Incorrect async function binding (func vs coroutine parameters in LangChain’s Tool class)

    Schema validation errors caused by the LLM generating malformed JSON inputs

    Version mismatches and evolving library APIs causing subtle bugs