agents

An OTP-native Elixir library for building AI agents, durable LLM workflows, retrieval pipelines, and production LLM services.

Open-source runtime for multi-agent AI systems with job scheduling, DAG orchestration, shared memory, tool execution, and real-time observability.

A vocabulary-driven graph memory library for AI agents, with storage backends, indexing pipelines, and MCP servers for building persistent structured memory into agent workflows.

OpenAI’s SDK docs for programmatically controlling local Codex agents, with coverage of setup, core concepts, tools, orchestration, evaluation, and deployment paths.

CLI for testing and improving documentation with simulated developer agents. It checks whether docs are clear enough for agents to complete real tasks, reports where they get stuck, and can generate proposed edits.

Open-source, self-hostable sandbox for AI agents. It lets agents work inside isolated Linux containers through MCP tools, with CLI and host-level admin controls for creating, managing, and exposing boxes.

Dream Server is an open-source stack that turns a PC, Mac, or Linux machine into a private AI server with local model inference, chat UI, voice, agents, workflows, RAG, and image generation. The page shows setup instructions, platform support, release notes, and a clear positioning for self-hosted use.

Zero is an experimental programming language for agents, with a compiler, standard library, docs, examples, and CLI commands for checking, running, building, and inspecting programs.

A web utility for creating end-to-end encrypted share links for single-file HTML generated by agents. It stores ciphertext for seven days and lets browsers decrypt and render the page from the URL fragment in a sandbox.

Open-source, self-hosted CLI and platform for tracking how ChatGPT, Claude, Gemini, Perplexity, and local LLMs cite a site, with dashboards, API endpoints, MCP support, and reporting workflows.

An open-source TypeScript framework for building reactive AI agents around a shared agentic environment. The README explains the event model, participant types, and basic installation and usage.

AutoGPU is an open-source project for using AI agents to design and harden a GPU-like chip end to end, from Verilog through synthesis and place-and-route to GDSII. The repo shows a concrete fp8 matmul accelerator flow, quick-start steps, and documentation for running the design/hardening process.

Self-hosted AI workspace with chat, agents, deep research, document editing, email triage, notes, calendar, and model comparison. The README includes setup instructions for Docker and native installs, plus a broad feature list and demo references.

TypeScript SDK for building agent skills as typed state machines, with workflow steps, schema validation, branching, testing helpers, and packaging into distributable executables.

A tool that converts any URL into markdown optimized for coding agents, with browser, CLI, API, SDK, and agent integration support.

A research report on the current MCP ecosystem, with live crawl numbers, verification rates, category breakdowns, and examples of both strong and weak MCP-positive sites.

Appaca is an AI workspace for operators that lets teams build internal tools, custom workflows, and specialized AI co-workers by chatting with AI. The page shows examples across sales, finance, marketing, HR, ops, product, engineering, and IT, plus support for knowledge bases, built-in storage, automations, and integra

Rapunzel is an open-source desktop app for managing agent sessions in a tree-style terminal interface. The README explains its purpose, install steps, launch commands, build instructions, and the core features: branchable terminal sessions, workspace persistence, and session management actions like rename, move, collap

A tool that analyzes local Claude Code logs to show where tokens, time, and cost go across a month of usage, including re-reading context, cache reads/writes, and subagent activity.

An essay arguing that the BEAM runtime and OTP primitives map well to agent workloads, especially long-lived personal-assistant agents with supervision, registries, and structured concurrency.

A curated learning roadmap for building production AI agents, covering OpenAI, Anthropic, MCP, harnesses, evals, memory, and safety. The README organizes the material into phases with exercises and a prioritized reading table.

A blog post about an experimental local LLM system where three qwen3.5:9b agents run autonomously, maintain stress states, self-modify capabilities, and coordinate through a shared OS-like layer.