Discover the Best AI Resources

FastMCP

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.

Project AIRI

A self-hostable virtual companion: a VRM or Live2D character you own that voice-chats in real time, plays Minecraft and Factorio, and runs models in-browser via WebGPU or across 25+ LLM providers like Ollama, OpenAI, and Claude.

OpenUI — The Open Standard for Generative UI

Generates structured, streaming UIs from LLM output and renders them in React using a compact OpenUI Lang, built component libraries, and chat surfaces; claims up to ~67% token savings vs JSON and includes a playground and CLI.

Structured 3D Latents for Scalable and Versatile 3D Generation

Generates high-quality, editable 3D assets from text or images and decodes to radiance fields, 3D Gaussians, or textured meshes. Ships pretrained models up to 2B parameters, a 500K asset dataset and training code; best used with image conditioning and a ≥16GB NVIDIA GPU.

Basic Memory

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.

AI Engineering (AIE) — book and companion resources

Companion resources for Chip Huyen's AI Engineering book: chapter summaries, study notes, prompt examples, case studies, and a few analysis scripts. Focuses on engineering practices for adapting foundation models to production rather than step-by-step code tutorials.

MCP Atlassian

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.

Local Deep Researcher

Runs iterative, fully-local web research loops using locally hosted LLMs (via Ollama or LMStudio): it auto-generates search queries, gathers and summarizes results, reflects to find gaps, re-queries, and emits a final markdown report with sources.

mcp-server-browserbase

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.

Forge: AI-Enhanced Terminal Development Environment

Terminal-native AI coding agent that brings conversational, multi-model code assistance into your shell. Integrates with 300+ models and providers, offers an interactive TUI, Zsh ':' plugin, semantic workspace search, and Git-oriented workflows for in-terminal edits, commits, and command suggestions.

AI Data Science Team

A library of specialized AI agents that automate data science steps: loading, cleaning, wrangling, feature engineering, SQL queries, EDA, and ML modeling via H2O and MLflow. Higher-level analyst workflows chain these under a supervisor agent.

Jido

Elixir-native autonomous agent framework that models state changes as pure cmd/2 operations and describes side effects with typed directives; integrates with OTP supervision and optional LLM plugins for AI-driven agents.