ACI: Unified Infrastructure for Model‑Context‑Protocol (MCP) Servers

A common pain point in building AI assistants is the need to stitch together dozens of APIs, each with its own authentication flow and data format. ACI.dev tackles this by acting as a single, secure gateway that exposes over 600 pre‑built integrations to any agent or IDE. By consolidating OAuth, secret management, and permission handling into one place, developers can focus on crafting the conversational logic of their assistants rather than wrestling with token refreshes and rate limits.

The core of ACI is a Unified MCP server that presents tools as first‑class function calls. When an assistant decides to schedule a meeting or query Slack, it simply invokes a declarative function name and arguments. The MCP server translates this into the correct HTTP request, applies tenant‑specific credentials, and returns a structured response. This abstraction keeps agents agnostic to the underlying platform—whether they are running on OpenAI, Anthropic, or a self‑hosted LLM—and guarantees consistent error handling and retry logic across all integrations.

Key capabilities include:

• Dynamic Tool Discovery – Agents can list available tools at runtime, enabling context‑aware decision making and reducing the need for hard‑coded tool lists.
• Granular Permissions – Natural‑language permission boundaries let developers define what actions a user or bot can perform, with the MCP enforcing these rules automatically.
• Multi‑tenant Auth – Built‑in OAuth flows and secrets storage support both developer accounts and end‑user credentials, making it trivial to scale from prototyping to production.
• SDK Flexibility – For lightweight use cases, the Python SDK offers direct function calls without running a full MCP server, yet still benefits from the same security model.

Real‑world scenarios that thrive with ACI include:

• VibeOps Automation – An AI assistant can provision cloud resources, configure databases, and deploy containers by calling platform‑specific tools through the MCP, turning a prototype into a live product in minutes.
• Enterprise Tool‑Calling – A corporate chatbot can securely access Salesforce, Jira, and Confluence with a single unified interface, ensuring compliance and auditability.
• Rapid Prototyping – Developers can spin up a local MCP server, connect to 600+ services instantly, and iterate on agent behavior without writing boilerplate authentication code.

By integrating ACI.dev into an AI workflow, teams gain a robust, extensible foundation that eliminates repetitive plumbing, enforces security best practices, and accelerates time‑to‑value for agentic applications.