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Anthropic enhances Claude Managed Agents with two new privacy and security features - 9to5Mac
Anthropic is introducing two new features for Claude Managed Agents that give users more control over the security and privacy. Anthropic unveiled Claude Managed Agents in April, greatly simplifying the work required to build and deploy cloud-hosted AI agents. Earlier this month, Managed Agents went even further with new dreaming, outcomes, and multiagent orchestration features. Now Anthropic is adding two additional new features for May: MCP tunnels and self-hosted sandboxes. "Both the sandbox where an agent executes tools and the services it reaches run within the established boundaries of your enterprise, under your security and runtime controls," Anthropic says. The new MCP tunnels feature allows Claude Managed Agents users to route services through a private network. With MCP tunnels, your agents reach MCP servers inside your private network without exposing them to the public internet. Internal databases, private APIs, knowledge bases, and ticketing systems become tools your agents can call. A lightweight gateway you deploy makes a single outbound connection, no inbound firewall rules, no public endpoints, and traffic encrypted end to end. MCP tunnels is a limited research preview, so requesting access is required before getting started for now. Meanwhile, the new self-hosted sandbox feature lets you easily set boundaries for Claude Managed Agents. With self-hosted sandboxes, you keep sensitive files, packages, and services in your own infrastructure or with a managed sandbox provider. The agent loop that handles orchestration, context management, and error recovery stays on Anthropic's infrastructure, while tool execution moves to your own configured environment. Self-hosted sandbox supports bringing your own sandbox client or using one of Anthropic's partners: Cloudflare, Daytona, Modal, and Vercel. Self-hosted sandboxes arrive as a public beta feature. You can learn more about both updates to Claude Managed Agents here. Recent Anthropic news: Separately, research scientist and OpenAI founding team member Andrej Karpathy has joined Anthropic after being independent for some time:
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Securing AI agent credentials with MCP tunnels
The reason enterprises have been slow to connect AI agents to internal APIs and databases isn't the models -- it's the credentials. In most production deployments, the agent carries authentication tokens with it as it executes tool calls, which means a compromised or misbehaving agent takes the keys with it. Anthropic is addressing that problem with two new capabilities for Claude Managed Agents: self-hosted sandboxes, which let teams run tool execution inside their own infrastructure perimeter, and MCP tunnels, which connect agents to private MCP servers without exposing credentials in the agent's context. Together they move credential control to the network boundary rather than leaving it inside the agent. Right now, self-hosted sandboxes are available to Claude Managed Agent users in public beta, while MCP tunnels are currently in research preview. Anthropic isn't the only model provider making this bet. OpenAI added local execution to its Agents SDK in April in response to similar demand. The architectural distinction Anthropic draws is a split: the agent loop runs on Anthropic's infrastructure, while tool execution runs on the enterprise's own system -- a separation that existing sandbox approaches, including OpenAI's, don't make. The architecture problem in sandboxes and agents MCP moved to enterprise production faster than the security architecture around it matured. In most deployments, credentials travel through the agent itself as it executes tool calls against internal systems -- meaning a compromised or misbehaving agent has everything it needs to cause damage. Self-hosted sandboxes, such as those offered on Claude Managed Agents, help keep files and packages within an enterprise's infrastructure. The agentic loop -- orchestration, context management and error recovery -- moves to the platform, and ideally, enterprises control compute resources. This allows the agent to complete tool calls without holding the keys that unlock it. Private network connectivity works similarly -- a lightweight outbound-only gateway inside the organization's network, with no credentials passing through the agent. Orchestration teams get some control For orchestration teams, the capabilities represent more than just a security update; they help agents run better. But the first thing they need to understand is how this split architecture can affect their deployment. Since sandboxes determine tool execution locations and the resources agents access, and MCP tunnels tell agents how to reach internal systems, these are separate concerns -- splitting them up enables enterprises to map agents' workflows more effectively. For teams already on Claude Managed Agents, the practical starting point is sandboxes -- move tool execution onto your own infrastructure and test the boundary before touching MCP tunnels, which are still in research preview. Teams evaluating the platform for the first time should treat the sandbox architecture as the primary technical differentiator: it's the piece that changes the threat model, not just the deployment model.
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Anthropic introduces two privacy and security features for Claude Managed Agents that address a critical enterprise concern: credential exposure. MCP tunnels enable private network connectivity without exposing internal systems, while self-hosted sandboxes keep tool execution within enterprise infrastructure. These updates move credential control to the network boundary rather than leaving authentication tokens inside the agent.
Anthropic has introduced two privacy and security features for Claude Managed Agents designed to address a fundamental barrier slowing enterprise AI agent deployments: the risk of credential exposure
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. The new capabilities, MCP tunnels and self-hosted sandboxes, shift how enterprises manage AI agent security by separating where agents orchestrate from where they execute tools. In most production deployments today, agents carry authentication tokens as they execute tool calls, meaning a compromised or misbehaving agent effectively takes the keys with it2
. This architectural vulnerability has kept enterprises cautious about connecting AI agents to internal APIs and databases, even as the underlying models have grown more capable.
Source: VentureBeat
The MCP tunnels feature allows Claude Managed Agents users to route services through a private network without exposing internal systems to the public internet
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. With MCP tunnels, agents can reach MCP servers inside private networks and access internal databases, private APIs, knowledge bases, and ticketing systems as tools they can call. The implementation relies on a lightweight gateway that enterprises deploy, which makes a single outbound connection with no inbound firewall rules and no public endpoints, while traffic remains encrypted end to end1
. This approach moves credential control to the network boundary rather than embedding it within the agent's context2
. MCP tunnels is currently available as a limited research preview, requiring access requests before teams can begin implementation.
Source: 9to5Mac
The self-hosted sandboxes feature lets enterprises set boundaries for Claude Managed Agents by keeping sensitive data, files, packages, and services within their own infrastructure or with a managed sandbox provider
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. The architecture splits responsibilities: the agent loop that handles orchestration, context management, and error recovery stays on Anthropic's infrastructure, while tool execution moves to the enterprise's own configured execution environment1
. This separation allows agents to complete tool calls without holding the authentication tokens that unlock access to sensitive systems2
. Self-hosted sandboxes arrive as a public beta feature and support bringing your own sandbox client or using partners including Cloudflare, Daytona, Modal, and Vercel.Related Stories
For orchestration teams managing enterprise AI agent deployments, these capabilities represent more than a security update—they fundamentally change the threat model by enabling better agent workflow mapping
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. Since sandboxes determine tool execution locations and the resources agents access, while MCP tunnels define how agents reach internal systems, splitting these concerns enables enterprises to map agents' workflows more effectively. Anthropic positions this split architecture as a key differentiator from other approaches. OpenAI added local execution to its Agents SDK in April in response to similar demand, but Anthropic draws an architectural distinction: existing sandbox approaches, including OpenAI's, don't separate the agent loop from tool execution in the same way2
. For teams already using Claude Managed Agents, the practical starting point is sandboxes—moving tool execution onto their own infrastructure and testing the boundary before exploring MCP tunnels, which remain in research preview. Teams evaluating the platform for the first time should treat the sandbox architecture as the primary technical differentiator, as it changes the threat model rather than just the deployment model.Summarized by
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