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Cloudflare, a connectivity and cloud company, recently debuted new cloud offerings designed to accelerate the development of AI agents.

Remote MCP servicer, new Workflows, and more are now available for organizations

The offerings include the industry’s first remote Model Context Protocol (MCP) server, generally available access to durable Workflows, and a free tier for Durable Objects. They are designed to enable developers to easily build agents in minutes and deploy powerful AI agents simply, affordably, and at scale.

“Cloudflare is the best place to build and scale AI agents. Period. The most innovative companies out there see that agents are the next big frontier in AI, and they’re choosing Cloudflare because we’ve got everything they need to move fast and build at scale on our Workers platform,” said Matthew Prince, co-founder and CEO of Cloudflare. “Cloudflare was built for this moment. First, we built the most interconnected network on the planet. Then, we built a developer platform that took advantage of that network to run code within 50 milliseconds of 95 percent of everyone online. And, we’re keeping our foot on the gas to give developers the best tools to build the future of agentic AI.”

Cloudflare’s Developer Platform will address some of the most significant challenges that exist in building AI agents through:

  1. Unlocking smart, autonomous actions with the industry’s first remote MCP server

MCP is an open-source standard that allows AI agents to interact directly with external services. This shifts AI from giving instructions to actually completing tasks on a user’s behalf.

Through these offerings, Cloudflare facilitates the construction and deployment of remote MCP servers, enabling any AI agent to securely connect via the internet and interact with services without needing a locally-hosted server. Cloudflare also streamlines authentication and authorization through partnerships with Auth0, Stytch, and WorkOS, which allow users to delegate permissions to agents, significantly simplifying the secure deployment of agents.

  1. Offering Durable Objects on Cloudflare’s free tier to build intelligent, contextually aware AI agents

Developers can now access Durable Objects on Cloudflare’s free tier, previously available only as part of paid plans. This expansion broadens and democratizes access to a critical component for building agents. Durable Objects are unique Cloudflare Workers that combine compute with storage, allowing users to create stateful applications in a serverless environment without managing infrastructure.

Additionally, Durable Objects provides a foundation for AI agents that require maintaining context across interactions, while Cloudflare’s network ensures scalability to millions of simultaneous customer interactions. It can operate agents close to the original request, guaranteeing each customer receives a fast, low-latency response.

  1. Workflows speed deployment, scale resources as needed, and optimize cost

These Workflows will allow users to build multi-step applications that can automatically retry, persist, and run for minutes, hours, days, or weeks. They also provide developers and organizations with a way to build and manage multi-step AI-powered applications.

Cloudflare’s serverless platform will automatically scale inference and AI agent resources based on demand, from zero to global scale in milliseconds.

This will ensure that organizations only pay for what they use, dramatically reducing costs compared to traditional cloud deployments that require constant provisioning.

“Cloudflare offers a developer-friendly ecosystem for creating AI agents that includes a free tier for Durable Objects and serverless options for AI inference,” said Kate Holterhoff, senior analyst at RedMonk. “These low-cost, easy-to-use options could empower more businesses to adopt and experiment with agentic AI.”

The rise of AI has ignited organizations’ desire for solutions that help them develop their own AI agents. Read more about new auditable AI agents launched by FloQast for accountants.

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