Reference architectures and microservices for building GPU-accelerated vision agents that enable natural-language video search, long-video summarization, visual Q&A, and alert verification. Integrates NVIDIA NIM models, embeddings, VLMs/LLMs, and agent workflows for deployable video-analytics stacks.
Converts PDF, Office docs, EPUB, images, audio, HTML and ZIP archives into structured Markdown for LLM pipelines, preserving headings, tables and links instead of visual layout. Adds optional OCR, audio transcription and LLM image captions.
Orchestrates configurable deep-research agent workflows that combine LLMs, web search, and MCP tools to produce structured research reports and evaluation outputs. Supports LangGraph Studio, multiple model providers (OpenAI, Anthropic, local models), and Deep Research Bench evaluation for benchmarked comparisons.
Brings an agentic chat experience to the terminal: describe a task in natural language and it plans, edits files, and runs commands to build the app. Written in Rust, ships on macOS and Linux. Now succeeded by the closed-source Kiro CLI.
Official remote MCP servers that let AI agents read and change Cloudflare config in natural language — managing Workers and bindings, querying observability and DNS analytics, searching docs. Each capability is a separate scoped server.
Expose Python functions as MCP‑compliant servers and clients so LLMs can call tools and resources directly; includes automatic schema generation, input validation, transport negotiation, authentication, and in‑conversation interactive UIs.
Provides a local-first Markdown knowledge graph that LLMs and humans can both read and write via the Model Context Protocol (MCP). Features two-way, editable notes, semantic search (embeddings + hybrid ranking), and optional cloud sync and team workspaces.
Bridges AI assistants to Jira and Confluence via the Model Context Protocol, exposing ~72 tools for JQL search, issue/page CRUD, status transitions, and comments. Supports Cloud and Server/Data Center with API-token, PAT, or OAuth 2.0 auth.
Exposes a managed cloud browser to an LLM as MCP tools, letting an agent open sessions, navigate, click, read page elements, and pull data from live websites. Built on Stagehand, so steps are written in plain language, not brittle CSS selectors.
Connects an AI agent to a Supabase project over MCP to run SQL, manage tables and migrations, deploy Edge Functions, fetch keys and types, and read logs. Read-only mode and project scoping cap what the agent can touch.
Full-stack AI red‑teaming platform that fingerprints AI infrastructure for known CVEs, audits MCP servers and agent skills with LLM-driven analysis, and runs cross-model jailbreak evaluations; designed for hands-on security assessment of AI deployments.
Build scripts that repackage Anthropic's Claude Desktop into native Linux artifacts (.deb, .rpm, AppImage, AUR, Nix flake), enabling a native Claude client with system tray, global hotkey, and MCP integration for Debian/Ubuntu and other distros.