Exposes internal databases, HTTP APIs, and files to LLM agents over MCP, with auto-generated schemas, access controls, rate limiting, redaction, and audit logging.
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.
MCP server providing managed persistent memory for AI agents. Read and write structured state across sessions, tools, and restarts at 1000+ requests per second, with no infrastructure to self-host or operate.
Enables deployment of autonomous AI agents with memory and tool execution capabilities through a WebSocket-based MCP protocol. Provides production-ready infrastructure with REST API access, persistent state management, and extensible function registry for building self-hosted AI systems.
Turns existing backend APIs (OpenAPI) and SQL databases (PostgreSQL, MariaDB, ClickHouse) into hosted MCP servers for AI clients, with built-in dashboards, forms, and credential encryption.
Enables AI agents to securely call enterprise MCP tools with tenant-scoped RBAC, human approvals, audit logging, and multi-tool workflows across customer, order, document, and ticket data.