process message special WhatsApp Business

The problem

LLM agents often lack a standardized way to interface with custom backend operations, leading to messy prompt loops and inconsistent data handling. Developers need a predictable bridge between natural language requests and structured execution without manual parsing overhead.

What it does

• Standardizes calls to the process_message MCP tool using structured JSON envelopes.
• Manages conversational state and token isolation via session identifiers.
• Handles errors gracefully using pre-defined codes like RATE_LIMITED and MISSING_PARAM.
• Integrated caching mechanism to reduce redundant processing and upstream latency.
• Ensures offline execution for operations that do not require external network access.

Frameworks & tools

MCP (Model Context Protocol), JSON, and local MCP server environments.

Why this beats prompting it yourself

Direct prompting often fails to maintain state or handle complex error codes reliably. This skill provides a schema-first approach that forces the agent to return valid JSON results while managing session memory across multiple turns, something raw prompts struggle to do consistently.

Use cases

• Executing custom internal business logic through a unified MCP interface.
• Maintaining user-specific state and data cursors in long-running agent chats.
• Building reliable wrappers for sensitive operations that require strict error reporting.
• Reducing latency by serving repeated identical requests from the built-in cache.

Known limitations

Requires an active MCP server running the process_message tool. State is only maintained as long as the MCP server remains operational.