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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 →
434 repos · 24 topics · curated by ShipWithAI · new: OpenShell, SkillOpt, Meshy →

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.

Kimi K3 (2.78T-parameter MoE) inference in portable C99 on one CPU: the dense trunk stays in RAM, 4-bit experts stream from disk, and output is byte-identical from 8 GB to 224 GB.
Serverless platform for agent sandboxes: stateful Firecracker microVMs with snapshots, cloning, auto suspend/resume and network policy, plus fan-out orchestration functions. Python SDK and CLI.
Memory and context engine for AI: fact extraction, user profiles, contradiction handling and forgetting, hybrid RAG + memory search, connectors, agent plugins and a one-binary local mode.

Renmin University's self-evolving ontology layer for data agents: builds a workload-grounded ontology over tables, files and databases, serves it via MCP, and evolves it from agent trajectories.
Rust RDF graph database and SPARQL 1.1 engine on RocksDB, with Python (pyoxigraph), JavaScript/WASM bindings and a CLI server, plus reusable crates for RDF parsing, serialization and SPARQL.

Coordination protocol for parallel coding agents above Git: agents declare intent in a shared SQLite store, and a deterministic detector flags plan collisions before code is written.
Local inference desktop app + CLI: profiles your hardware, estimates tok/s per model before download, tunes the one you pick, and connects Pi, OpenCode, Hermes, Codex or Claude Code in a click.

Markdown notes as a knowledge graph: an LSP for VS Code, Neovim, Zed and Helix, plus CLI and MCP so AI agents query the same files by structure. Rust, local-first, OKF-compatible.
Minimal TypeScript reference implementation of the Operational Ontology pattern behind Palantir Foundry: shared objects and links, action-gated writes, business rules, audit and write-back.

WhipCode: open-source coding agent in Go built on a recursive language-model loop; agents delegate to sub-agents through short programs, with daemon-owned sessions across desktop, TUI and web.
CNCF tool that syncs infrastructure assets and relationships (AWS, GCP, Azure, Kubernetes, GitHub, Okta and 30+ more) into a Neo4j graph, then runs security rules and Cypher queries over it.

Bend 2: a Python-like language with dependent types that compiles to fast CPU/GPU code; LAWS.bend declares invariants the compiler forces AI-written code to prove before it builds.

Embeddable semantic layer for AI agents: define metrics once, compose them with expressions and time shifts, row-level security and read-only SQL, over MCP, REST, CLI, Python or a Postgres facade.
Rust OLTP graph database on object storage with native vector and BM25 search: property graph, traversal-prefiltered ANN and full-text in one transactional engine; Rust, TS, Go, Python SDKs.
Cross-harness memory for coding agents: captures sessions from Claude Code, Cursor, Codex and 20+ harnesses, distills reviewed knowledge over MCP/skills, and forwards telemetry to SIEMs.

Desktop app implementing Karpathy's LLM Wiki pattern: an LLM ingests your documents into a persistent, interlinked wiki with a knowledge graph, hybrid search, deep research and an MCP server.
Microsoft's trigram-indexed grep: a client/server index narrows each regex to candidate files. Powers search in GitHub Copilot CLI; ships MCP tools and hooks for Codex and pi. Rust.

Mark Burgess's Semantic Spacetime knowledge graph on Postgres: write notes in the N4L language, compile them into a story graph, then search, browse and path-solve it via Go API or web UI.
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