Dedalus Labs

Dedalus Labs is the AI-native cloud platform built for developers who are ready to move beyond fragmented toolkits and rapidly deploy complex agentic AI applications. It serves as a comprehensive, drop-in infrastructure layer that unifies the entire agent lifecycle—models, tools, and orchestration—into a single, high-efficiency system. Dedalus Labs solves the costly challenges of setup overhead, vendor lock-in, and infrastructure management, allowing you to ship powerful agents faster than ever before.

Key Features

Dedalus Labs provides the essential components necessary to streamline agent development, ensuring speed, flexibility, and scalability without the typical infrastructure burden.

• ⚡ Rapid Agent Building & Deployment: Transition from concept to functioning agent in minutes, not weeks. The powerful Agents SDK allows you to build and deploy sophisticated agents, equipped with any model and any tool, using just 5 lines of code. This eliminates the need for complex Docker files, intricate YAML configurations, and time-consuming setup.

• 🌍 Universal Model Access and Flexibility: Achieve true vendor agnosticism and eliminate model lock-in. With a single line of code, you can instantly swap between leading LLMs—such as GPT-5, Claude Opus 4.1, Gemini 2.5 Flash, or Qwen-Max—to optimize for cost, latency, or performance without rewriting your core logic.

• ⚙️ 3-Click Managed MCP Server Deployment: Deploy the infrastructure your agents need instantly. Dedalus Labs manages your Model Context Protocol (MCP) servers, allowing you to spin up a fully hosted server from a GitHub repo in just three clicks. This includes automatic health checks, global autoscaling, and a clean MCP endpoint, all without requiring any Docker files or manual setup.

• 🤝 Hosted MCP Marketplace and Tooling: Instantly equip your agents with production-ready tools built by the community. Access a marketplace of publicly listed MCP servers (e.g., web search, code execution, data analysis) and call them with a single slug, bypassing the need to worry about configuration, formats, or proprietary protocols.

Use Cases

Dedalus Labs is designed to accelerate critical development workflows, turning complex orchestration into simple API calls.

1. Accelerate Prototyping and Time-to-Market

When you need to test a new agentic workflow, Dedalus Labs enables rapid iteration. Instead of spending days configuring infrastructure, you can define your agent's logic, select a model, and integrate a marketplace tool in minutes using the 5-line SDK. This allows teams to transition from an initial idea to a functioning agent with tools in the hands of testers within the same day.

2. Seamlessly Integrate Local and Cloud Tools

Use the SDK to combine local Python functions (e.g., internal data processing scripts) with cloud-hosted MCP servers from the marketplace. The Dedalus Labs infrastructure intelligently handles all routing, load balancing, and hand-offs between these disparate tool types, ensuring seamless execution regardless of where the tool resides.

3. Maintain Flexibility and Cost Optimization

For production agents, quickly swap the underlying LLM based on real-time cost analysis or performance metrics. If a new, more efficient model is released, you can update your deployment with a single line of code, instantly leveraging the new capability without the massive migration effort usually associated with changing model providers.

Why Choose Dedalus Labs?

Dedalus Labs is engineered specifically to address the complexity and fragmentation inherent in the current AI agent ecosystem, providing a developer-first platform that emphasizes speed and control.

• Drop-in Unification Layer: Dedalus Labs acts as a single MCP gateway and Agents SDK that unifies fragmented models and tools. This open-source, vendor-agnostic approach supports model handoffs, chaining of both local and hosted components, and real-time streaming across any provider—all through one reliable API endpoint.

• Simplicity and Speed: We prioritize developer experience by eliminating infrastructure friction. The ability to build and deploy complex agents in 5 lines of code and manage MCP servers in 3 clicks means you spend zero time on Docker files, YAMLs, or wasted setup weeks, dramatically improving development velocity.

• Managed Scalability and Reliability: When you deploy an MCP server through Dedalus Labs, you automatically gain critical production features like health checks and global autoscaling. This managed infrastructure ensures your tools and agents are always available and performant, allowing you to focus purely on agent logic.

Conclusion

Dedalus Labs provides the robust, flexible, and simplified infrastructure layer developers need to harness the full potential of agentic AI. By unifying the fragmented ecosystem and removing setup barriers, we empower you to build composable, scalable, and powerful AI applications effortlessly.

Explore how Dedalus Labs can accelerate your development: Install the open-source SDK today.