Product updates, implementation guides, and ideas for shipping Model Context Protocol servers faster.
Organizations deploying autonomous assistants face a governance gap: an agent may draft text safely in isolation but create materially different risks once it can send email, edit...
Connector endpoints can turn a useful Model Context Protocol (MCP) deployment into a path to sensitive context, privileged tools, and reusable credentials if authorization,...
Autonomous AI assistants are moving beyond simple chat interfaces. They can write and debug code, manage email and calendar activity, work with internal data, and shop for goods....
Model connector deployments allow large language models (LLMs) to retrieve context, call APIs, query data stores, trigger workflows, and use external services. That capability can...
Autonomous systems can create real enterprise value when they move work forward across data, tools, applications, and workflows. They can also create a new operational problem:...
Large language model toolchains increasingly act as operational control planes. They route requests, select tools, request authorization, hold state, call external services, and...
Autonomous assistants are moving beyond chat interfaces. They can act across email, calendars, code repositories, procurement flows, support systems, and other connected tools,...