Enables policy-style auditing of content through the audit_vibe MCP tool to enforce configurable guardrails. Supports both local stdio and serverless Streamable HTTP deployment via Vercel for flexible integration with MCP clients.
Provides real-time content security for large language models by identifying and intercepting risks across compliance, ethics, and safety dimensions. It enables secure input and output monitoring through a customizable policy engine using an SSE-based interface.
Enables observability and governance for local LLMs via Ollama, including auditing model usage, scanning prompts for secrets/PII, and enforcing allow/deny policies.
Provides a sequentialthinking tool for dynamic, reflective problem-solving via chain-of-thought reasoning. Supports local Stdio and remote SSE deployment on Google Cloud Run.
Exposes the MiniMax M3 LLM API to MCP-compatible clients, enabling chat completions, text completions, tool calls, and token counting via stdio or SSE transport.
