Fastn UCL
Fastn UCL is a secure, enterprise-grade multi-tenant Model Context Protocol (MCP) that enables seamless connection of AI agents to various tools and platforms.
About Fastn UCL
Fastn UCL is a robust, enterprise-ready multi-tenant Model Context Protocol (MCP) designed for SaaS applications. It provides a unified command interface that connects AI agents to a wide range of tools, APIs, and platforms. Acting as a central orchestration layer, Fastn UCL ensures secure, scalable, and resilient infrastructure with features like built-in authentication, comprehensive monitoring, and schema flexibility. Its design simplifies managing complex AI workflows without ongoing maintenance, making it ideal for large-scale enterprise deployments.
How to Use
Start by securely linking your internal tools and external services through Fastn UCL. Connect your MCP-compatible AI agents to the unified gateway, then embed the React component into your applications. Fastn UCL manages authentication, routing, and permissions, providing real-time monitoring of AI actions across over 1000 tools and platforms with a centralized dashboard.
Features
- Schema-flexible, AI-optimized architecture for dynamic data handling
- White-labeled embedded app store for AI agent integrations
- Unified Command Layer (UCL) for commanding any system or tool
- Managed, zero-maintenance infrastructure
- Developer-friendly SDKs and APIs
- Single orchestration layer supporting Slack, CRMs, Jira, LLMs, and more
- AI Action Agent for executing real-world tasks like messaging or record creation
- Enterprise-grade security and multi-tenancy support
- Context-aware command routing based on tenant configurations
- Automated OAuth credential management
- Advanced monitoring, logging, and observability tools
- Built-in authentication, authorization, and access controls
- Connects AI agents to over 1000 tools, APIs, and platforms
- Highly scalable, resilient infrastructure suitable for enterprise needs
Use Cases
- Enabling secure multi-tenant AI applications to access sensitive enterprise data and workflows.
- Allowing AI agents to perform actions such as messaging or data entry based on user permissions.
- Integrating multiple data sources into a unified API for AI-driven automation.
- Connecting AI agents to popular enterprise tools like Slack, Gmail, Snowflake, CRMs, and Jira.
- Embedding white-labeled app stores within products for secure tool integration.
- Monitoring AI activity, tool usage, and performance across tenants via a centralized dashboard.
Best For
Pros
- Complete white-label customization for embedded app stores
- Managed infrastructure eliminates the need for local MCP servers
- Handles dynamic schemas and data changes without disruption
- Strong security standards including SOC 2, ISO, GDPR, HIPAA, and PCI
- Advanced enterprise authentication and access controls
- 24/7 technical support and deployment assistance
- Unified API and orchestration layer for efficient tool management
- Low latency responses under 100ms with 99.9% uptime SLA
- Supports thousands of users and hundreds of tools with high scalability
- Real-time monitoring, detailed logging, and audit capabilities
- Built-in multi-tenancy for data separation and tenant-specific workflows
Cons
- No specific limitations are mentioned; primarily highlights benefits and enterprise readiness.