What is the difference between Static and Dynamic modes?

In **static mode**, the server provides all available tools from your integrations. In **dynamic mode**, it offers an 'enable-tools' utility, allowing AI agents to request and enable specific tools on-demand for a given session.

Does it support persistent chat sessions?

Yes, the server includes experimental support for persistent chat sessions via the Streamable HTTP transport. You can use an 'x-chat-id' header to maintain conversation context across requests.

How does it expose tools for AI agents?

It implements the Model Context Protocol (MCP) to present actions from your Integration.app connections as structured tools. AI agents can then use these tools to interact with various services and perform tasks.

What is the Integration App MCP Server?

It's a Model Context Protocol (MCP) server that transforms actions from your connected Integration.app integrations into discoverable tools for AI agents and Large Language Models (LLMs).

What are the prerequisites to use the Integration App MCP Server?

You'll need Node.js (v18 or higher) and an active Integration.app account to connect your integrations and generate an access token for authentication.

Integration App

Name: Integration App
Author: membranehq

bymembranehq

•

Desarrollo de API

Ciencia de Datos y ML

Herramientas para Desarrolladores

Exposes actions from connected integrations on Integration.app as tools for AI agents via the Model Context Protocol.

Integration App

bymembranehq

•

Desarrollo de API

Ciencia de Datos y ML

Herramientas para Desarrolladores

Exposes actions from connected integrations on Integration.app as tools for AI agents via the Model Context Protocol.

The Integration App MCP Server acts as a Model Context Protocol (MCP) server, designed to bridge your connected integrations on Integration.app with AI agents. It transforms the capabilities of various integrated services into 'tools' that AI models can discover and utilize. Supporting both static mode (providing all available tools) and dynamic mode (allowing selective tool enablement), it offers flexibility for diverse AI applications. The server leverages Streamable HTTP for efficient communication, handles authentication with Integration.app access tokens, and even includes experimental chat session management for persistent conversations.

Características Principales

01Offers Streamable HTTP (recommended) and Server-Sent Events (SSE) transports for communication.

02Includes experimental chat session management for persistent conversations across requests.

03Implements the Model Context Protocol (MCP) for AI agent tool provision.

04Exposes actions from Integration.app connections as discoverable tools for Large Language Models (LLMs).

0524 GitHub stars

06Supports both static (all tools) and dynamic (on-demand tool enablement) modes for tool fetching.

Casos de Uso

01Providing a standardized Model Context Protocol interface for AI tools within an application.

02Enabling AI agents to automate tasks and interact with various Integration.app services.

03Building custom AI-powered applications that require programmatic access to real-world integration actions.