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A curated map of open-source AI & agent tools. Every connection is a typed, human-reviewed relationship — with the why written down. How we curate →
452 repos · 24 topics · curated by ShipWithAI · new: moli, edgextract, lift →

Rust headless browser for AI agents on Servo/Stylo components: fetch pages as Markdown or a semantic tree, automate via CDP, WebDriver or BiDi — about 13% of Chrome's memory per task.

Markdown to knowledge graph with an ontology you write: a small local decision model answers closed yes/no questions per candidate, and your cutoff keeps, queues for review or drops each link.

Datalab's 9B vision model that extracts JSON matching your schema from PDFs and images in one pass — schema-constrained decoding, multi-page values, vLLM or HF inference, Schema Studio.

Cache-to-Cache (ICLR'26): LLMs talk by projecting and fusing each other's KV-caches instead of generating text — higher accuracy than text relay at ~2x lower latency. Fuser weights on HF.
NVIDIA's security scanner for agent skills: 71 patterns across 17 categories — prompt injection, exfiltration, supply chain, MCP tool poisoning — static plus optional LLM pass, SARIF output.
Low-latency, multi-tenant property graph database that runs queries as sparse-matrix linear algebra (GraphBLAS); OpenCypher over the Redis protocol, built for GraphRAG and agent memory.
Strands Agents: open-source Python and TypeScript SDK for building and running agent harnesses in your process — model-agnostic, with lifecycle controls, hooks, MCP, multi-agent and tracing.
Strands' small decision model (2B, Qwen3.5-based): pick between options, answer yes/no or rate on a scale with calibrated confidence. CLI and /v1/systemone server on CUDA, MPS, MLX or CPU.
Project-based course on harness engineering for coding agents: 14 lectures, 8 projects on tools, state, verification and loops, plus breakdowns of Claude Code, Codex and Pi. 15 languages.
Apache Ossie (incubating, formerly Open Semantic Interchange): a vendor-neutral JSON/YAML spec for exchanging semantic models across BI, analytics and AI tools, with reference converters.

Rust agent harness built for fleets: desktop app, terminal or embeddable library, with built-in memory, browser/desktop control, 119 OAuth apps and 14 channels — 500 agents on a $10 VPS.
Microsoft's Go CLI for agent-skill quality: scaffold eval suites from SKILL.md, run them through Copilot, grade, compare models, replay snapshots and check spec and token budgets.
AG-UI, the Agent-User Interaction Protocol: ~16 standard event types that stream agent runs into frontends — chat, shared state, generative UI, frontend tools, human-in-the-loop.

Skill + local tool to review HTML and Markdown like a Google Doc: edit text, drag blocks, comment on elements, then send every change to your coding agent in one batch.

Intent compiler skill for coding agents: probes your repo, asks only what no file answers, halts on ambiguity, and emits a typed IntentSpec it later checks the delivered work against.

141k-star collection of 100+ runnable AI agent, agent-skill and RAG app templates — clone one, pip install, run — across Claude, Gemini, GPT and open models. Apache-2.0.

Google Research's Regularized Recursive Self-Improvement: evolves an agent harness (prompts, tools, memory, sub-agents) with constraints on the search so gains hold out of distribution.

Find code by asking what it does: `jg` uses the Jev decision model to judge folders, files and declarations, returning relevant files plus verbatim excerpts for coding agents. CLI + skill.

NVIDIA's safe runtime for autonomous agents: kernel-enforced sandboxes with policy on every file, syscall and connection; credentials injected only for approved endpoints.
Microsoft's text-space optimizer that trains a frozen agent's skill document like weights — rollouts, bounded edits, validation-gated updates — and ships a compact best_skill.md.

OpenBMB's RL training framework where every role — inference, training, rollout — is an independent service talking over one TransferQueue data plane. Built on SGLang and torchtitan.

vLLM's programmable decision layer: one endpoint for your agent harness that selects or combines models per call by policy — quality, latency, cost, location — across local and cloud backends.
Pick any model for any coding agent from one menu-bar app: a local gateway translating OpenAI, Anthropic and Gemini APIs, with subscription sign-ins and quota failover across accounts.

Self-hosted crew of AI agents on an org chart sharing one long-term memory: delegation, mid-task model switching, 1,000+ app connectors, reachable from terminal, WhatsApp, Telegram or Slack.

Block's self-hostable workspace where humans and agents share rooms on a Nostr relay — chat, canvases, workflows, patches and reviews as signed events; agents join with their own keys.
Self-learning skill layer for Claude Code: distills skills from your real sessions, merges same-scenario ones, updates them in use and prunes the unused — touching only skills it wrote.
Lossless long-term memory for a personal AI: verbatim JSONL logs, time-first search over SQLite FTS5 (sqlite-vec as last resort) and a tiny 'where are we now' index injected every turn.

Hooks Claude Code, Codex, OpenCode and Pi so every edit is checked against the rules in your AGENTS.md/CLAUDE.md by a decision model (Jev) — ~300 ms per check, violations fixed in-turn.

Office SDK for embedding spreadsheets, docs, slides, bases and PDFs in your own product — canvas rendering, formula engine, plugins and one Facade API across browser and Node.js.

Contrastive Language Models: CLM-8B, an open System-1 decision model scoring states against actions — typed choice/score/yes-no answers on a TypeSafe-compatible API, up to 9x faster than Jev.

Continual-learning byte-level LM trained from scratch on one 8 GB GPU: weights page in from disk, capacity grows and prunes itself while it keeps reading a single data stream.
Computer-use infrastructure for agents: sandboxed Linux, macOS and Windows desktops locally or in the cloud, Cua Driver for native apps (CLI/MCP/SDK), Lume VMs, CUA-S1 models, Cua Bench.
LlamaIndex's local document parser in Rust: PDFium text with bounding boxes at ~2-5 ms/page, selective Tesseract or HTTP OCR, Markdown/JSON output, screenshots; Python, Node, WASM.
Google's declarative runtime for agent workloads on Kubernetes: Task, Workspace and Model manifests run each agent sandboxed on Agent Substrate, with suspend/resume and ax ssh.

Nokia research: turn any open LLM into a Jev-style decision model. Typed choice, yes/no or score from one prefill, de-biased with no labels or a fitted head, served on vLLM.

Non-autoregressive decision engine: typed choice, score and yes/no answers over text in one forward pass (~33 ms), 100+ languages, calibrated probabilities, a router picking the checkpoint.
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