# aci

> MCP Server

AI agent integration platform. Connects agents to 600+ tools via MCP server with auth & permissions. Function calling & VibeOps.

## Overview

- **Category:** AI
- **Language:** Python
- **Stars:** 4889
- **Forks:** 386
- **Owner:** aipotheosis-labs
- **GitHub:** https://github.com/aipotheosis-labs/aci
- **Homepage:** https://www.aci.dev/
- **Created:** 2024-09-19T15:06:53+00:00
- **Updated:** 2025-07-07T16:51:49+00:00
- **Source:** https://model-context-protocol.com/servers/aci

## Setup

## Setup

To run the full ACI.dev platform (backend server and frontend portal) locally, follow the individual README files for each component:

- **Backend:** [backend/README.md](backend/README.md)
- **Frontend:** [frontend/README.md](frontend/README.md)

**Note:** The specific prerequisites, configuration requirements, and environment variables will be detailed in the respective `README.md` files for the backend and frontend components. Please refer to those files for detailed instructions.

## Tools

## Available Tools & Features

ACI.dev provides a comprehensive suite of tools and features designed to streamline the development and deployment of AI agents and VibeOps workflows.

**Core Features:**

*   **600+ Pre-built Integrations:** Connect to a vast ecosystem of services and applications, including Google Calendar, Slack, Notion, and more. This eliminates the need to build custom integrations from scratch.
    *   **What it does:** Provides pre-configured connections to popular services, enabling AI agents to interact with them seamlessly.
    *   **Usage Example:** An AI agent can use the Google Calendar integration to schedule meetings, check availability, and send invitations.
*   **Flexible Access Methods:** Choose between the Unified MCP Server for centralized management or the lightweight Python SDK for direct function calls.
    *   **What it does:** Offers multiple ways to interact with ACI.dev's capabilities, catering to different architectural preferences and performance requirements.
    *   **Usage Example:** Use the Python SDK for low-latency interactions within an existing agent framework, or leverage the MCP server for centralized control and management of multiple agents.
*   **Multi-tenant Authentication:** Securely manage authentication for both developers and end-users with built-in OAuth flows and secrets management.
    *   **What it does:** Simplifies the process of authenticating users and agents with various services, ensuring secure access and data privacy.
    *   **Usage Example:** Allow multiple users to connect their Google accounts to an AI agent without exposing their credentials directly to the agent.
*   **Enhanced Agent Reliability:** Implement natural language permission boundaries and dynamic tool discovery to improve agent performance and security.
    *   **What it does:** Enables fine-grained control over agent capabilities, preventing unintended actions and ensuring that agents only access the tools they need.
    *   **Usage Example:** Restrict an AI agent to only access specific Google Calendar events or prevent it from sending emails without explicit user confirmation.
*   **Framework & Model Agnostic:** Integrate ACI.dev with any LLM framework and agent architecture, providing maximum flexibility and avoiding vendor lock-in.
    *   **What it does:** Ensures compatibility with a wide range of AI development tools and platforms, allowing developers to choose the best tools for their specific needs.
    *   **Usage Example:** Use ACI.dev with Langchain, LlamaIndex, or any other LLM framework to build powerful AI agents.
*   **100% Open Source:** Benefit from a transparent and community-driven platform with all components (backend, dev portal, integrations) released under the Apache 2.0 license.
    *   **What it does:** Provides full access to the source code, allowing developers to customize and extend the platform to meet their specific requirements.

**Use Case Specific Tools (via Integrations):**

*   **Web Search:** Search the web for information using integrations with search engines like Google or DuckDuckGo.
    *   **What it does:** Allows agents to gather information from the internet.
    *   **Usage Example:** A research agent can use web search to find relevant articles and data on a specific topic.
*   **Calendar Management:** Manage calendars, schedule meetings, and send invitations using integrations with Google Calendar or Outlook Calendar.
    *   **What it does:** Enables agents to automate calendar-related tasks.
    *   **Usage Example:** A personal assistant chatbot can schedule meetings based on user requests and availability.
*   **Email Communication:** Send and receive emails using integrations with Gmail or Outlook.
    *   **What it does:** Allows agents to communicate with users and other systems via email.
    *   **Usage Example:** An outbound sales agent can send personalized emails to potential leads.
*   **CRM Integration:** Update and manage customer data in CRM systems like Salesforce or HubSpot.
    *   **What it does:** Enables agents to automate CRM-related tasks.
    *   **Usage Example:** A customer support agent can update customer records based on interactions.
*   **Document Management:** Interact with documents stored in services like Google Docs or Notion.
    *   **What it does:** Allows agents to access and manipulate documents.
    *   **Usage Example:** A research agent can sync research results to a Notion page.
*   **Code Execution:** Execute code snippets in various programming languages.
    *   **What it does:** Enables agents to perform complex calculations and data processing.
    *   **Usage Example:** A vibeops agent can execute terraform code to provision infrastructure.