Frontapp MCP Server

The Frontapp MCP Server is a dedicated bridge that connects large language models to the Frontapp customer communication platform. By exposing a rich set of MCP tools, it allows AI assistants to read, create, and modify conversations, contacts, tags, inboxes, and user data directly from within a natural‑language workflow. This eliminates the need for developers to write custom API wrappers or handle authentication logic, letting them focus on crafting conversational experiences.

For developers building AI‑powered customer support or sales workflows, the server solves a common pain point: integrating an external SaaS platform into a conversational context. Frontapp’s API is REST‑based and requires OAuth tokens, pagination handling, and webhook verification. The MCP server encapsulates all of this complexity behind a simple set of tools that follow the Model Context Protocol, making it trivial for an LLM to fetch the latest inbox state or append a tag to a conversation with just a single tool call.

Key capabilities include:

• Conversation, Contact, and Tag Management – Retrieve lists, create new threads, update existing records, and manage tagging in bulk.
• Inbox and User Access – Query inbox metadata and fetch user profiles to personalize interactions.
• Real‑time Webhook Processing – Listen for Frontapp events (new messages, status changes) and push them into the LLM’s context so that the assistant can react instantly.
• Secure Credential Handling – Store API keys encrypted with AES‑256 and verify webhook signatures to protect sensitive data.
• HTTPS Support – All traffic is encrypted with TLS/SSL, ensuring compliance with modern security standards.

In practice, the server empowers scenarios such as a virtual support agent that can automatically categorize incoming tickets, a sales bot that pulls contact details to personalize outreach, or an internal tool that updates conversation tags based on sentiment analysis performed by the LLM. By integrating seamlessly into existing MCP‑enabled workflows, developers can augment Frontapp’s native features with AI logic without touching the underlying platform code.

The architecture is modular: an API gateway routes requests from LLMs and webhooks, dedicated handlers translate those into Frontapp API calls, and a client layer abstracts the HTTP interactions. This separation makes it straightforward to extend the server with additional tools or swap out the underlying SDK if Frontapp releases a new version. Overall, the Frontapp MCP Server turns a complex customer‑communication API into a first‑class conversational resource that AI assistants can query, update, and react to in real time.