Product updates, implementation guides, and ideas for shipping Model Context Protocol servers faster.
Model endpoints are where sensitive prompts, retrieval context, tool outputs, proprietary weights, and authorization decisions meet. Confidential compute for model endpoints can...
Autonomous assistants become difficult to trust the moment they can search private knowledge, call APIs, modify records, send messages, or initiate transactions. Autonomous...
Shadow tools do not need to bypass an agent’s runtime controls if they can enter through a trusted-looking catalog, manifest, or deployment workflow. Agent tool registry hardening...
Autonomous agents can now initiate workflows, call APIs, retrieve information, and carry out transactions across connected systems. The difficult question is no longer whether an...
Stateless connectors can make AI integrations easy to scale, but they can also turn a stolen bearer token, an overly broad tool grant, or a misplaced context payload into an...
Autonomous systems cannot earn meaningful trust if other systems cannot determine who is acting, what that actor is allowed to do, and what evidence remains after an action is...
Hosted inference platform compliance is not solved by selecting a provider with strong certifications. Teams must decide what each tenant can share, where data can be processed,...
Autonomous assistants can take useful action across APIs, cloud services, internal tools, and MCP servers, but a record showing that “the agent did it” is rarely enough....
Protecting sensitive contexts in model integration endpoints requires more than filtering a user’s last prompt. The decisive security boundary is everything the model can see,...