Fastn UCL

Fastn UCL is a secure, enterprise-grade, multi-tenant Model Context Protocol (MCP) for SaaS, designed to seamlessly connect AI agents to the tools, APIs, and platforms users rely on. It functions as a Unified Command Layer (UCL), acting as a multi-tenant MCP gateway and orchestration layer that provides a consistent interface for commanding any system (e.g., Slack, Gmail, Snowflake, internal APIs). Fastn UCL offers built-in authentication, monitoring, observability, and multi-tenancy by design, ensuring enterprise-readiness, resilient infrastructure, and an AI-optimized, schema-flexible approach with zero maintenance.

## How to Use

To use Fastn UCL, you first connect your apps by linking internal tools and external services through a secure, unified connection. Then, you embed Fastn UCL by connecting your MCP-compatible AI agent to Fastn's unified gateway and embedding their React component for user app connections. This process provides secure multi-tenant access to over 1000 tools, with Fastn handling authentication, routing, and permissions. The system allows for monitoring of AI agent actions in real-time from a unified dashboard.

Fastn UCL's

## Key Features

- Secure, enterprise-grade, multi-tenant MCP for SaaS - Unified Command Layer (UCL) for commanding any system - Connects AI agents to 1000+ tools, APIs, and platforms - Built-in authentication, authorization, and access control - Intelligent monitoring, logging, and observability - Enterprise-grade scalability and resilient infrastructure - AI-optimized, schema-flexible design for dynamic data - Zero maintenance (managed infrastructure) - Embedded App Store for AI Agents (white-labeled) - Single Orchestration Layer for various tools (Slack, CRMs, Jira, LLMs) - AI Action Agent for taking real actions (e.g., sending messages, creating records) - SDKs and APIs available for developers - Context-Aware Execution for routing commands based on tenant configuration - Automatic OAuth management

## Use Cases

- Connecting AI agents to a wide range of user tools and enterprise systems (e.g., Slack, Gmail, Snowflake, CRMs, Jira, LLMs). - Enabling AI agents to perform real actions like sending messages or creating records based on user authorization. - Embedding white-labeled app stores directly into products for users to securely connect tools their AI agent needs. - Integrating and orchestrating multiple data sources into a single, unified API for AI agent interaction. - Providing secure, multi-tenant access for AI products to interact with sensitive enterprise data and workflows. - Monitoring and debugging AI agent actions, tool usage, and performance across all tenants from a unified dashboard.

## FAQ

**?** What is MCP? Is UCL secure?