Tag

Rowboat

Connects to Gmail, Calendar, and meeting notes to build a local, Obsidian-compatible Markdown graph it acts on — drafting emails, briefs, and decks. Memory accumulates instead of resetting each session; runs on local or hosted models, extensible via MCP.

fast-agent documentation

MCP-native agent framework built around the Model Context Protocol from the start, with end-to-end tested Sampling and Elicitation. Define agents and multi-step workflows in Python, run terminal-first, and swap Anthropic, Google or local models.

Verifiers: Environments for LLM Reinforcement Learning

Bundles a dataset, an interaction harness, and rubric-based reward functions into one RL environment for training and evaluating LLMs — also usable as an eval, synthetic-data pipeline, or agent harness for any OpenAI-compatible endpoint.

Cloudflare Agents

Runs stateful AI agents as Cloudflare Durable Objects — each keeps its own storage and lifecycle, hibernating when idle and waking on demand. Adds WebSocket state sync, type-safe RPC, resumable LLM streaming, MCP roles, and durable workflows.

Neuro SAN Studio

Hands-on studio to design, test and deploy declaratively configured multi-agent systems built on the Neuro SAN framework. Ships ready examples, an Agent Network Designer UI (nsflow), CLI tooling, and integrations with major LLMs and external tools for rapid prototyping.

AutoAgent

Lets you build, generate, and run multi-agent LLM workflows from natural-language prompts with no coding. Automatically profiles agents, creates tools/workflows, and supports multiple LLM providers plus CLI/Docker deployment.

Vexa

Runs a self-hosted meeting bot and transcription API that joins Google Meet, Teams and Zoom and streams speaker-attributed transcripts in real time. Compiles meetings into a git-backed Markdown workspace and runs sandboxed agents on your infrastructure; Apache-2.0 and air-gap capable.

DeepChat

Desktop AI client that unifies cloud and local LLMs, tool calling (MCP), installable Skills, and ACP agent integration into a single multi-window workspace. Supports local Ollama models, multi-provider configuration, remote control, and privacy-focused local storage.

Awesome AI Apps

Curates 80+ hands-on LLM-powered examples, tutorials and recipes for building agents, RAG systems, voice assistants, and agentic workflows. Includes starter templates, course playlists, and reference apps for rapid prototyping and learning.

PRIME-RL

An asynchronous, high-throughput framework for large-scale reinforcement learning and agentic training that scales to 1T+ MoE models and 1000+ GPUs, with native verifiers integration, end-to-end SFT/RL/evals, and Slurm/Kubernetes deployment; requires NVIDIA GPUs.

Hands-On AI Engineering

Curated collection of production-oriented AI projects that implement OCR, RAG, multi-agent systems, and multimodal pipelines. Each entry provides runnable code, setup notes, and engineering patterns to help developers move prototypes toward production.

OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Coordinates role-playing agents to automate real-world tasks — web search and browsing, code execution, document parsing, and multimodal handling. Built on the CAMEL-AI framework; scored 69.09% on the GAIA benchmark, topping open-source frameworks.