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Builds production-grade AI agents and multi-agent workflows in .NET and Python, with graph-based orchestration for sequential, concurrent, and handoff patterns. Unifies Microsoft's Semantic Kernel and AutoGen lineages, adding durable, checkpointed runs.
Official reference code for building browser-controlling agents on Google's Gemini computer-use models. The model sees a screenshot, proposes a UI action, and the loop executes its clicks, typing and scrolling via local Playwright or cloud Browserbase.
Drops Claude Code into GitHub Actions so it responds to @claude mentions in PRs and issues — answering questions, reviewing diffs, and committing fixes or features on a branch. Runs on your runners via the Anthropic API, Bedrock, or Vertex AI.
Provides a community-curated database of AI model metadata—specs, pricing, and capabilities—and exposes it via a JSON API and a TOML-based contributor workflow for programmatic lookup and integration.
Turns commodity WiFi Channel State Information into spatial sensing: 17-keypoint pose estimation, presence detection, and contactless breathing/heart-rate monitoring through walls, with no camera. Runs on a mesh of ESP32-S3 nodes (~$9 each).
Run Claude as a programmatic agent in Python: one-shot query() calls or a stateful ClaudeSDKClient for multi-turn loops. Define in-process tools, lifecycle hooks, and per-tool permissions; it bundles the Claude Code CLI and exposes its full toolset.
Demonstrates orchestration of specialist customer-service agents built with the OpenAI Agents SDK, pairing a Python backend for agent logic with a Next.js UI (ChatKit) to visualize routing, guardrails, and demo flows. Useful for prototyping multi-agent customer-service workflows; uses mock flight data and requires an OpenAI API key.
Provides a visual, low-code environment to build, debug, and deploy AI agents—integrates model services (OpenAI, Volcengine), RAG, plugins, workflows, and a Chat SDK for embedding agents into apps.
Exposes Google Analytics Admin and Data APIs as a local Model Context Protocol (MCP) server so LLMs can query accounts, run reports, funnels and realtime queries via standardized MCP tools. Intended for local prototypes and developer integrations; requires Google Cloud credentials.
An open-source memory layer that turns agent runs and conversations into structured, persistent state recallable across sessions. Captures facts, events, preferences, and relationships automatically; LLM-agnostic with SDK and MCP integration.
Reviews each pull request for security issues: Claude reads the diff and flags vulnerabilities like injection, auth flaws, and hardcoded secrets as inline comments, with built-in false-positive filtering. Ships as a GitHub Action or slash command.