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Bifrost is the open-source AI gateway for building a complete AI audit trail and governing every AI interaction, from the data center to every laptop. Most enterprises can account for only a fraction of the AI requests their employees send each day, because the only traffic that gets logged

Bifrost is one control plane for governing AI coding agents like Claude Code, Cursor, and Codex, with Bifrost Edge extending it to every machine. AI coding agents like Claude Code, Cursor, and Codex now run across hundreds or thousands of developer machines in a typical engineering organization, and most of

Bifrost is the open-source AI gateway that governs MCP security risks centrally, while Bifrost Edge extends that same governance to every endpoint machine. The Model Context Protocol (MCP) lets AI applications discover and call external tools at runtime, which means every connected MCP server becomes a new trust boundary

MCP server governance controls which MCP servers, tools, and users are allowed across your AI traffic. Bifrost enforces it at the gateway and the endpoint. Most organizations cannot produce a list of the MCP servers running inside the AI tools their employees use every day. Model Context Protocol (MCP) servers

Bifrost governs shadow MCP by inventorying every ungoverned MCP server configured across your fleet and enforcing allow or deny policy on each device. Shadow MCP is the set of Model Context Protocol (MCP) servers that employees connect to their AI tools without any security or governance layer in between. These

Bifrost is the AI gateway and policy engine for governing AI in the browser, with Bifrost Edge extending those controls to ChatGPT web, Claude.ai, and beyond. Most enterprise access to generative AI now happens inside the browser. Menlo Security's 2025 research found that roughly 80% of generative

Governing Claude Desktop in enterprises means routing its AI traffic through Bifrost. The gateway sets policy; Bifrost Edge enforces it on every machine. Claude Desktop is installed on engineering and knowledge-worker laptops across most enterprises, and in many of those organizations nothing sits between the app and the model