Demonstrates stateful application patterns on the stateless MCP 2026-07-28 protocol, enabling request-scoped state, multi round-trip confirmations, and streaming progress updates across independent tool calls.
Enables MCP-compatible AI clients to invoke CLI-driven agent tools over Streamable HTTP, including shell execution, file operations, patching, image viewing, web search, and nested agent tasks, with permission modes and real-time progress streaming.
Enables AI agents to securely discover, invoke, and manage tools through a hardened MCP endpoint with protections like injection detection, circuit breakers, retry backoff, response caching, context-window limiting, and state snapshots.
Enables an LLM to dynamically discover and call tools across multiple MCP servers (file, GitHub, SQL, Python execution) with authentication, rate limiting, and observability, supporting parallel execution and secure deployment.
