Search results for "safety"
Plano is an AI-native proxy and data plane for agentic apps — with built-in orchestration, safety, observability, and smart LLM routing so you stay focused on your agents core logic.
A secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, Telegram, WhatsApp, Discord, Teams, and MCP tools. Secure by design, runs on you
Memory that lasts and compounds. MentisDB gives agents durable memory so they do not just remember, they improve over time. It stores append-only thought chains plus a Git-like skills registry, lett
EdgeCrab 🦀 A Super Powerful Personal Assistant inspired by NousHermes and OpenClaw — Rust-native, blazing-fast terminal UI, ReAct tool loop, multi-provider LLM support, ACP protocol, gateway adapters
Autonomous AI agent that contributes to open source — discovers repos, analyzes code, generates fixes, and submits PRs
The official Rust SDK for the Model Context Protocol
Fast, small, and fully autonomous AI personal assistant infrastructure, ANY OS, ANY PLATFORM — deploy anywhere, swap anything 🦀
Frontier self improving AI intern / coworker
An AI agent for teams, communities, and multi-user environments.
TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.
Serialize your functions with tools-rs!
Local AI anywhere, for everyone — LLM inference, chat UI, voice, agents, workflows, RAG, and image generation. No cloud, no subscriptions.
Open-source autonomous AI assistant with 5-tier security, 62 tools, 14 LLM providers. Written in Rust. Single binary.
Add formal type safety (10 levels, dependent/linear/session types) to any query language — SQL, GraphQL, Cypher, SPARQL, VQL
Add provably safe ethical constraints to AI agents via Phronesis
Add consent patterns and accessibility to existing code via WokeLang
Extract state machines from code and model-check with TLA+/PlusCal
🦀 Prevents outdated Rust code suggestions from AI assistants. This MCP server fetches current crate docs, uses embeddings/LLMs, and provides accurate context via a tool call.