Secure, local and programmable sandboxes for AI agents — launch hardware-isolated microVMs in sub-100ms to execute untrusted code

Model Context ProtocolAI AgentsDocker

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The official Rust SDK for the Model Context Protocol, providing both client and server implementations with full support for Tools, Resources, Prompts, Sampling, OAuth, and more.

Model & Inference FrameworkAI AgentsSDK

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A local code knowledge graph tool built on Tree-sitter that provides precise context to AI coding assistants via MCP, achieving an average 8.2× token reduction with support for 24 programming languages.

Model Context ProtocolRustCLI

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An official Datadog CLI tool optimized for AI Agents, featuring 200+ commands across 33+ products, structured output, Runbooks automation, and WASM execution.

SDKAI AgentsRust

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Open-source LLMOps platform with a Rust high-performance gateway unifying LLM access, observability, evaluation, optimization, and experimentation

Model & Inference FrameworkLarge Language ModelsRust

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Persistent memory engine for AI coding agents featuring auto-capture hooks, triple-stream hybrid retrieval, and 4-tier memory consolidation to eliminate re-explanation across sessions.

Docs, Tutorials & ResourcesRAGModel Context Protocol

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A local-first context runtime for AI coding agents that significantly reduces token consumption from file reads and shell outputs via multi-strategy compression and property graph techniques, compatible with 28+ AI coding tools including Cursor, Claude Code, and Copilot.

Model Context ProtocolAI AgentsRust

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An Agent-First IDE for Vibe Coding, enabling parallel multi-project workflows with multiple Claude Code and Codex agents.

Multi-Agent SystemAI AgentsRust

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A terminal session manager for AI coding agents, featuring a TUI and Web Dashboard for parallel multi-agent orchestration, tmux persistence, Docker sandboxing, and remote access.

Multi-Agent SystemAI AgentsDocker

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A type-safe domain-specific language for LLMs that transforms prompt engineering into schema engineering, compiling to native-typed clients in multiple languages for reliable structured LLM output.

Model & Inference FrameworkSDKLarge Language Models

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