Stop building your AI stack from 40 open tabs.
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 →
Start here: Build a coding agent →
254 repos · 19 topics · curated by ShipWithAI · new: opc-skills, reverse-skill, statewright →
new: your agent can query the map — npx -y @ship-with-ai/stackmap-mcpconnect →

Ten agent skills for solopreneurs — SEO/GEO, Reddit/X/Product Hunt research, domain hunting, logo and banner generation, session archiving — installable in Claude Code, Cursor and 16+ tools.

Reverse-engineering and pentest skill router for coding agents: routes APK/ELF/JS/PCAP/CTF tasks to the right playbook, bootstraps jadx/Frida/IDA-class toolchains, evolves a knowledge base. CN/EN.

State-machine guardrails for AI agents: define workflow phases once and only that phase's tools unlock — enforced across Claude Code, Codex, Cursor, opencode and Pi. Rust.

All-in-one AI framework around an embeddings database — dense, sparse, graph and relational fused — with pipelines, workflows, agents and MCP/web APIs. Python, bindings for JS/Java/Rust/Go.
Indexes the session histories your coding agents already wrote — 17 harnesses, months retroactive — and serves recall over MCP. 84.9% hit@1 on LongMemEval-S, no LLM, no embeddings. One Go binary.

Rust MCP server + desktop Studio for AI-native ontology engineering: 70+ tools over an in-memory Oxigraph store — OWL2-DL tableaux reasoning, SHACL, SPARQL, versioning. Single binary, no JVM.

One installer that turns a PC, Mac or Linux box into a private AI server: Ollama, Open WebUI, n8n, ComfyUI wired together — inference, chat, voice, agents, RAG and image gen, no cloud.

PostgreSQL extension adding graph search, traversal and shortest-path over your existing tables — a derived graph index queried from plain SQL, no separate graph DB or query language. Rust.
Code-intelligence engine in one static Go binary: tree-sitter graph over 257 languages, compiler-grade resolution for 17, multi-repo, 175 configurable MCP tools — up to 50x fewer tokens. 100% local.

IBM's registry + proxy federating MCP, A2A and REST/gRPC into one governed endpoint: discovery, auth, rate limits, guardrails, OTel tracing, 40+ plugins — scales to K8s with Redis federation.
Distributed graph issue tracker for coding agents on Dolt: dependency-aware beads replace markdown plans — bd ready/claim/close, cell-level merge, push/pull across machines and agents. CLI + MCP.

Agentic formal verification: coding agents write TLA+ specs and invariants of your distributed system, model-check them, and reproduce violations at code level. arXiv paper + public bug list.

Modular local voice-agent pipeline — VAD→STT→LLM→TTS behind an OpenAI Realtime-compatible WebSocket; every stage swappable, the LLM slot takes any OpenAI-compatible server. Powers Reachy Mini robots.
Turns Databricks Unity Catalog tables into a materialized knowledge graph: OWL ontology design, R2RML mapping, OWL 2 RL/SWRL/SHACL reasoning, auto-generated GraphQL — exposed to agents over MCP.

GPU document parser in C++/TensorRT: PP-OCRv6 OCR, layout, tables and formulas to Markdown at 200-559 img/s on one GPU — no VLM, HTTP + gRPC, one-line Docker deploy.

Skill memory layer for agents: auto-captures learnings from runs into plain Markdown skill files you can read, edit, git and share across frameworks — memory without an opaque store.

One CLI gives agents read/search access to Twitter, Reddit, YouTube, GitHub, Bilibili and XiaoHongShu with zero API fees — multi-backend routing the maintainers repair when platforms break.

Parses a polyglot monorepo with Tree-sitter into a Memgraph knowledge graph: query it in plain English (NL→Cypher), trace data flow, find dead code, edit via AST-surgical patches.

KG-guided synthetic SFT data: builds a knowledge graph from source text, finds the LLM's knowledge gaps via calibration error, and generates targeted long-tail QA pairs. ACL-published.

LLM-driven Python scraping: describe what you want and graph pipelines extract structured data from websites or local docs (HTML, XML, JSON, Markdown). 29k stars; cloud API upsell.

Multiplayer agent harness for startups: every employee gets a scoped workspace — memory, files, keychain, crons, sandbox — in Slack and web, with Pi/OpenCode/Codex/Claude Code swappable underneath.

Rust framework for LLM apps: an agent harness, compile-time-typed task graphs, and streaming RAG pipelines — MCP toolboxes, human-in-the-loop approval, tracing with Langfuse support.

Context layer for large codebases: a graph of plain-English markdown nodes — no embeddings, no index — agents read like any repo file. Claude Code hooks + MCP; 42% fewer tokens in its bench.
LobeChat's 80k-star pivot: from chat UI to 'Chief Agent Operator' — hire, schedule and supervise a team of agents running 7×24, self-hosted via Docker or Vercel, plugin ecosystem carried over.

Local-first cost ledger for AI coding: reads the session files 36 tools already write and breaks every token and dollar down by task, model, project. TUI, web, desktop, menubar — no proxy, no keys.

Persistent memory for coding agents on the iii engine: MCP server with 53 tools, 12 auto-capture hooks, hybrid search + knowledge graph, zero external DBs. Claims 95% R@5 and 92% token cuts.
Turns your coding CLI into a job-search command center: scans Greenhouse/Ashby/Lever, scores listings A-F into a 1-5 rubric, tailors ATS-ready CVs, tracks applications. Claude Code, Codex, OpenCode+.
Single-file memory layer for agents: data, embeddings, index and metadata in one portable .mv2 — append-only Smart Frames, time-travel queries, sub-5ms recall, no server. Rust core, Node/Python SDKs.
Rust CLI proxy compressing dev-command output 60-90% before your agent reads it — git, tests, linters, docker, 100+ commands; hooks auto-rewrite bash calls. Single binary, <10ms overhead.
137k-star roster of specialist agent personas — engineering, design, marketing and ops divisions — installable into Claude Code, Cursor, Codex and 13+ tools via scripts or a native desktop app.
Claude Code config pack + optional local harness: TDD-enforcing hooks, 67 skills, quality gates, persistent memory — plus a dashboard routing each task across 13 models by cost-aware blast score.

Spec, task and memory layer that lives in your repo: .trellis/ holds conventions, PRDs and journals, auto-injected each session — one workflow across 20 coding-agent platforms.

YC-backed multi-agent harness for production: state an objective and the runtime compiles a graph DAG of specialized agents — role-based memory, crash recovery, cost limits, human-in-the-loop.

Rust coding-agent harness built for footprint: ~28MB per session vs 140-390MB for Codex/Claude Code, instant boot, optional local embeddings — made for running many sessions in parallel.

Runtime security for AI agents: watches actions AND reasoning traces to catch prompt injection, tool poisoning and out-of-remit behavior — blocking before the action lands. SDKs + Claude Code plugin.

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.
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