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A curated map of open-source AI & agent tools — and what actually pairs with what.
Every connection is a typed, human-reviewed relationship — with the why written down. How we curate →
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219 repos · 17 topics · curated by ShipWithAI · new: unstract, graph-engineering, Crucix →
new: your agent can query the map — npx -y @ship-with-ai/stackmap-mcpconnect →

LLM-driven platform turning unstructured documents into structured data: a no-code Prompt Studio to define extractions, then deploy as APIs or ETL pipelines. Self-hosted, AGPL + enterprise.
Graph engineering as a Claude skill: SEU's 9-stage knowledge-graph course (translated) plus task-graph orchestration patterns — with a teaching mode and nine paste-ready /kg workflows.

Self-hosted OSINT terminal: 27 open feeds — satellite fires, flights, radiation, sanctions, markets, conflict data — polled in parallel onto one Jarvis-style dashboard. LLM turns it two-way.

The first open foundation model for financial candlesticks: trained on K-lines from 45 global exchanges, AAAI 2026, weights on Hugging Face with fine-tuning scripts for your own tasks.

Aider woven into Emacs: AI pair programming with intelligent model selection, Ediff for reviewing AI changes, and file management that stays true to Emacs workflows. MELPA-packaged.

HKUDS's skill lifecycle layer for agents: retrieve the right skill per task, evaluate which ones actually work from real outcomes, share across agents and teammates, evolve with every run.

Hierarchical agent loops: nodes iterate toward a goal in their own git worktree and spawn children for subtasks — the tree grows to fit the problem. Hard caps, SQLite run log, live TUI.
Hugging Face's Python port of Pi's minimalist coding agent: a real terminal agent with TUI, sessions and skills — built to be READ, with a clean brain/environment/frontend separation.
Tokenization at GB/s: ~1000x faster than HuggingFace tokenizers with drop-in compatibility modes for HF and tiktoken — Rust reading your files directly. pip install gigatoken.

Agent multiplexer for your terminal: every Claude Code/Codex session in real panes — blocked/working/done at a glance, detach and reattach over SSH, plus a socket API agents drive themselves.

Runnable course: a production OCR pipeline on Kubernetes — Rust ingestion, Qwen 3.5 (4B) served by vLLM at 1.86 pages/s, Redis queues, KEDA autoscaling. Deploy it on AKS/GKE, not a notebook.

OpenAI's GitHub Action for CI hardening: bounded egress filtering and runner lockdown — the fence that keeps supply-chain attacks out and your CI-resident coding agent in.
Vectorless, reasoning-based RAG — builds a hierarchical tree index from long documents so an LLM retrieves by relevance instead of similarity. No chunking, no embeddings, no vector DB.

Rust memory layer for AI agents with Git-style version control — snapshot, branch, merge and rollback over MatrixOne's copy-on-write engine, plus hybrid vector + full-text retrieval.

From-scratch headless browser in Zig for AI agents and automation — CDP-compatible (Puppeteer/Playwright connect as-is) at ~9x the speed and ~16x less memory than headless Chrome.

Small Go HTTP/MCP server that gives AI agents direct control over Chrome — stealth CDP injection, multi-instance orchestration and a real-time dashboard. Local-first, single binary.

ruvnet's 65k-star 'agent meta-harness': multi-agent swarms, adaptive memory and RAG layered over Claude Code, Codex and Hermes — npx ruflo, a UI beta, and a sprawling plugin ecosystem.

The agentic HTML editor: your local coding-agent CLI (9 auto-detected, zero API keys) writes magazine pages, decks, posters and tweet cards via 75 skills — sandboxed preview, 1-click export.

Deterministic PDF parser for AI pipelines: #1 extraction accuracy (0.907) on its public bench, bounding boxes on every element, 0.015s/page — plus the first open PDF auto-tagging for accessibility.
CNCF-landscape sandbox platform for AI agents: multi-language SDKs, unified API, CLI and MCP over Docker/Kubernetes runtimes — coding agents, GUI agents, evals and RL training.
The 100-line agent from the SWE-bench team: >74% on SWE-bench Verified with no tools but bash, no config sprawl — the reference minimal harness, adopted by Meta, NVIDIA and Ramp.
Fully-local persistent memory for 14+ coding agents, built on an information-theoretic search engine — no vector DB, no API keys, no backend. pip install and your agents remember.
fork() for agent microVMs: children fork copy-on-write from a warm Firecracker parent — 100 KVM-isolated VMs in ~100ms, live-VM branching in ~56ms, portable snapshots from a hub.
Activeloop's shared brain for agent TEAMS: traces from Claude Code, Codex, Cursor & co become reusable skills every teammate's agent can execute — cloud-backed, 25% cheaper on LoCoMo.

The /last30days skill: researches any topic across Reddit, X, YouTube, HN, TikTok and Polymarket in parallel, scores by real engagement, and synthesizes one grounded brief. 50+ agent hosts.
Firecrawl's Rust PDF triage: classifies text-based vs scanned in ~10-50ms, extracts positioned text and clean Markdown without OCR — routing the ~54% of PDFs that never needed a model.

Roboflow's reusable computer-vision toolkit: one Detections API over any model (YOLO, SAM, transformers), 20+ annotators, zone counting, tracking and dataset tools. 48k stars, MIT.

htop for AI coding agents: every Claude Code, Codex and OpenCode session in one TUI — tokens, context-window %, rate limits, child processes, orphan ports. Read-only, no API keys. Rust.
Apple's official Core AI toolkit: recipes exporting Hugging Face models to .aimodel, PyTorch primitives for authoring, Swift runtime for macOS/iOS apps — plus skills for coding agents.
Rust 'software factory' for coding agents: define the SDLC as a graph, agents execute it through verification gates, you intervene only at the stages that matter. Server, runs board, sandboxes.
The 74k-star LLM-native crawler: turns any site into clean, RAG-ready Markdown — adaptive crawling, JS rendering, extraction strategies, Docker deploy. Python, Apache-2.0.

Code intelligence MCP in pure C: tree-sitter knowledge graph over 158 languages, average repo indexed in milliseconds, sub-ms queries, 10x fewer tokens. Single static binary, zero deps.

PM Skills Marketplace: 68 skills and 42 chained workflows in 9 plugins — discovery, strategy, PRDs, launch, growth — encoding Torres/Cagan-style frameworks for Claude Code and Cowork.

A skill that makes your agent code like the laziest senior dev: YAGNI enforced — ~54% less code, ~20% cheaper, ~27% faster on measured Claude Code sessions. Works with 20 agents.
Zilliz's unified memory for coding agents: one Markdown + Milvus store shared across Claude Code, Codex, OpenCode and OpenClaw — hybrid search, plus repeated workflows distilled into skills.

Self-improving loop from the SIA paper: Meta, Target and Feedback agents evolve a task agent's harness AND weights against a benchmark — #1 on MLE-Bench Hard, 14x kernel speedups.
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