ArchestackGitHub ↗ (opens in a new tab)

Agent backends

Agent templates and scaffolds (LangGraph, ADK, OpenAI Agents SDK, Cloudflare Agents, eve) meant to be extended.

eve-software-factory-template leads with 65, ahead of marketing-team-eve-template (59) and personal-agent-template (57). 18 projects ranked by score.

The ranking

Agent backends: full ranking
RankProjectAdoptionFreshnessMaintenanceEasy to runAgent-readyScore
1eve-software-factory-templateeve pipeline that turns GitHub or Linear issues into reviewed draft PRs1.2k stars, MIT, last commit Sep 20264610035677065 out of 100
2marketing-team-eve-templateeve lead agent delegating to five marketing specialists with approval gates450 stars, MIT, last commit Aug 20262610028677059 out of 100
3personal-agent-templateeve and Nuxt personal agent with Slack, GitHub, Linear and per-user memory477 stars, MIT, last commit Sep 20263010011677057 out of 100
#4adk-recipesRunnable Agent Development Kit recipes, from single patterns to deployable agents10.4k stars, Apache-2.0, last commit Oct 2026751006603053 out of 100
#5ai-townGenerative-agents town simulation on Convex with Ollama by default Live demo ↗ (opens in a new tab)10.6k stars, MIT, last commit Aug 2026781003617052 out of 100
#6knowledge-agent-templateNuxt knowledge agent that greps a synced snapshot repo instead of embedding1.1k stars, MIT, last commit Sep 20264310013333048 out of 100
#7OpenTagSlack and Teams knowledge agent on LangGraph and CopilotKit Channels1.3k stars, MIT, last commit Oct 2026501006703047 out of 100
#8react-agentMinimal Python LangGraph ReAct agent with Tavily, ready for Studio852 stars, MIT, last commit Oct 2026391003333047 out of 100
#9azure-ai-travel-agentsTravel-agency multi-agent sample using MCP servers in four languages483 stars, MIT, last commit Sep 20263310040174545 out of 100
#10openai-cua-sample-appComputer-use agent loops for Playwright browsers and PyAutoGUI desktops1.9k stars, MIT, last commit Sep 202660100460044 out of 100
#11data-enrichmentLangGraph agent that researches the web to fill your JSON schema258 stars, MIT, last commit Oct 2026131005033044 out of 100
#12agents-starterCloudflare Agents SDK chat starter with Durable Object state and scheduling1.3k stars, MIT, last commit Jul 202654100500043 out of 100
#13react-agent-jsTypeScript createAgent starter with example tools and middleware hooks118 stars, MIT, last commit Oct 202661005033042 out of 100
#14new-langgraphjs-projectEmpty TypeScript LangGraph.js scaffold with message history and tests75 stars, MIT, last commit Oct 202611005033041 out of 100
#15agent-starter-packGoogle Cloud agent scaffolder with Terraform, CI/CD and evals; now maintenance-only6.6k stars, Apache-2.0, last commit May 2026688600035 out of 100
#16new-langgraph-projectBlank Python LangGraph scaffold with config, tests and Studio support297 stars, MIT, last commit Oct 202617100380033 out of 100
#17claude-managed-agentsSelf-hosted control plane running Claude Managed Agents on Cloudflare Workers325 stars, MIT, last commit May 20262081003026 out of 100
#18openai-cs-agents-demoAirline support multi-agent demo with visible handoffs and guardrails6.6k stars, MIT, last commit Dec 2025712200021 out of 100

Momentum, Verified build, Docs and Privacy are not measured yet; their weight goes to the signals shown. A dash means the signal is not scored for that kind of project. Hover a number for its rating in words.

Reviews

165 out of 100

eve-software-factory-template

eve pipeline that turns GitHub or Linear issues into reviewed draft PRs

1.2k stars, MIT, last commit Sep 2026

An eve pipeline named Foreman: label an issue factory, @mention it, or delegate from Linear, and four agents (classifier, analyst, implementer, reviewer) each run in their own sandbox and end with a draft pull request on FACTORY_REPO. The reviewer sees only the pushed branch, a factory brain keeps notes about your repo between runs, and it deploys to Vercel with GitHub and Linear connectors. For teams piloting agent-written PRs with human merge.

Strengths

  • Reviewer is isolated from the implementer; verdicts are made against the real diff
  • Six entry points including red-CI self-repair on factory branches only
  • Local dev TUI treats runs as untrusted; GitHub writes wait for approval
  • Separate docs site; CLAUDE.md and AGENTS.md included

Weaknesses

  • Tied to eve, Vercel Connect, Vercel Sandbox and Vercel Blob
  • No model provider named in the README; model access comes through the Vercel stack
  • No tests listed
  • First task fails if the GitHub App cannot reach FACTORY_REPO; the error surfaces late
  • TypeScript, eve, ai-sdk
  • Needs vercel, github-app-connector, linear-connector, vercel-blob
  • GitHub template
  • env example file
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
259 out of 100

marketing-team-eve-template

eve lead agent delegating to five marketing specialists with approval gates

450 stars, MIT, last commit Aug 2026

An eve project where a lead agent briefs one of five specialists (product marketing, content, social, SEO, email) and returns their output as Notion pages, Typefully drafts or Resend campaigns through MCP connections. A shared brand context document in Vercel Blob is the only state, sends and scheduled publishes pause for approval in Slack or the terminal, and models come through Vercel AI Gateway. For teams studying multi-agent delegation.

Strengths

  • Approval matrix is enforced in connection tool lists, not only in prompts
  • Each specialist is a directory; the lead routes on its description alone
  • Remote agents let a specialist live in its own deployment
  • CLAUDE.md, AGENTS.md and architecture docs included

Weaknesses

  • Needs Notion, Resend and Slack connectors via Vercel Connect plus a Typefully key
  • Tied to eve, Vercel AI Gateway, Blob and Sandbox
  • No tests; pnpm validate covers lint and typecheck
  • No .env.example
  • TypeScript, eve, ai-gateway, ai-sdk
  • Needs vercel-connect, notion, resend, slack, typefully-api-key, vercel-blob, ai-gateway
  • GitHub template
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
357 out of 100

personal-agent-template

eve and Nuxt personal agent with Slack, GitHub, Linear and per-user memory

477 stars, MIT, last commit Sep 2026

A Nuxt app plus an eve agent runtime: Better Auth email login, web chat with threads that eve persists, Slack DMs and mentions linked to the same user, GitHub tools with durable approval on writes, Linear via Vercel Connect MCP, and a bounded per-user memory document in Vercel Blob. Postgres via Drizzle holds users and links; on Vercel it deploys as two services. For developers building a single-user or small-team assistant on eve.

Strengths

  • Memory is per authenticated principal, recalled before every turn and after compaction
  • Slack identity links to the web profile so context follows the user
  • Write actions on GitHub gate on durable approvals
  • CI workflow, CLAUDE.md and AGENTS.md present

Weaknesses

  • Needs Vercel Connect for Slack and Linear; self-hosting those integrations is on you
  • No model provider named in the README; configured through eve
  • No tests listed; CI covers typecheck and build
  • Requires Node 24+
  • TypeScript, eve, ai-sdk
  • Needs postgres, vercel-blob, vercel-connect
  • GitHub template
  • env example file
  • sign-in: Better Auth
Repository on GitHub ↗ (opens in a new tab)
#453 out of 100

adk-recipes

Runnable Agent Development Kit recipes, from single patterns to deployable agents

10.4k stars, Apache-2.0, last commit Oct 2026

A recipe collection for Google's Agent Development Kit: core/ holds single-pattern agents (OAuth flows, session memory, guardrails, RAG), contrib/ holds deployable vertical agents targeting Agent Engine, Cloud Run and Gemini Enterprise, and plugins/ holds skills packaged with SKILL.md and EVAL.yaml. Each recipe has its own README; ADK SDKs exist for Python, TypeScript, Go, Java and Kotlin. For teams standardizing on ADK and Google Cloud.

Strengths

  • Core recipes isolate one pattern each, so they lift cleanly into your project
  • Vertical agents include deploy paths to Agent Engine and Cloud Run
  • Recipe checklist and handbook define a contribution standard; tests and AGENTS.md included
  • Committed within the last day

Weaknesses

  • Root README is an index; no single app, no shared setup
  • Gemini and Google Cloud are the assumed model and deploy target
  • README states recipes are demonstrations, not for production use
  • Mixed languages and maturity across folders
  • Python, google, google-adk
  • Needs google-adk, google-api-key-or-vertex-ai
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#552 out of 100

ai-town

Generative-agents town simulation on Convex with Ollama by default

Live demo ↗ (opens in a new tab)10.6k stars, MIT, last commit Aug 2026

A deployable version of the Generative Agents paper: pixel-art characters on a PixiJS map that walk, talk and remember, driven by a simulation engine inside Convex, which is also the database and vector store. Models default to llama3 and mxbai-embed-large on Ollama, with OpenAI, Together or any OpenAI-compatible endpoint as env switches; Clerk auth was removed but the revert is documented. For teams building multi-agent simulations in TypeScript.

Strengths

  • Runs fully local with Ollama; docker compose self-hosts Convex, frontend and dashboard
  • Simulation state, transactions and vector memory all live in Convex
  • Live demo hosted by Convex
  • Characters and maps are data files (characters.ts, Tiled JSON)

Weaknesses

  • Convex is the backend; moving to another database means a rewrite
  • Changing the embedding model requires wiping all data
  • Auth was removed; re-adding Clerk is a git revert
  • README pins Node 18; last commit 2026-08
  • TypeScript, ollama, openai, together, openai-compatible
  • Needs convex, ollama-or-openai-compatible-api, replicate-optional
  • Docker
  • sign-in: Clerk
Live demo ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#648 out of 100

knowledge-agent-template

Nuxt knowledge agent that greps a synced snapshot repo instead of embedding

1.1k stars, MIT, last commit Sep 2026

A Nuxt monorepo where the agent answers by running grep, find and cat inside a pooled Vercel Sandbox holding a snapshot repo synced from GitHub repos, YouTube transcripts or custom sources by Vercel Workflow; there is no vector store. The same agent serves web chat, a GitHub bot and a Discord bot through Chat SDK adapters, with Better Auth (GitHub OAuth), an admin panel and a model router by question complexity. For teams whose docs already live in repos.

Strengths

  • No embeddings or vector DB; retrieval is deterministic and explainable
  • Admin panel with usage, errors, source sync and an admin agent over internal stats
  • Chat, GitHub and Discord share one agent; a new platform is one adapter file
  • Tests included; AGENTS.md and local skills for add-source and add-tool

Weaknesses

  • Built on Vercel Sandbox, Workflow and AI Gateway; self-hosting means replacing all three
  • Sandbox is shared and read-only; no per-user private sources
  • Auth is GitHub OAuth only
  • bun is the documented toolchain
  • TypeScript, ai-gateway, ai-sdk
  • Needs vercel-sandbox, vercel-workflow, ai-gateway-api-key, github-app
Repository on GitHub ↗ (opens in a new tab)
#747 out of 100

OpenTag

Slack and Teams knowledge agent on LangGraph and CopilotKit Channels

1.3k stars, MIT, last commit Oct 2026

A deployable Slack and Teams agent in two services: a Node runtime (CopilotRuntime with embedded Channels) and a Python LangGraph deep agent speaking AG-UI. It ships web research, optional GitHub, PostHog, Linear and Notion MCP tools, native Slack charts and a LangGraph interrupt that pauses before Linear or Notion writes, with Slack ingress through a CopilotKit Intelligence managed channel. For teams that want an on-call style bot in chat.

Strengths

  • Approval gate before writes is a resumable LangGraph interrupt, not a prompt rule
  • Railway config and an AWS ECS Fargate deployment are both in the repo
  • AGENT_URL accepts any AG-UI agent; the runtime does not care about the framework
  • Published container images; tests and AGENTS.md included

Weaknesses

  • Slack and Teams delivery depends on hosted CopilotKit Intelligence unless you build a runner
  • Two languages and two processes: Node 22 plus Python 3.12 with uv
  • OpenAI is the only documented model provider
  • Setup has several Slack-specific failure modes the README spends pages on
  • Python, openai, langgraph, ag-ui, copilotkit
  • Needs copilotkit-intelligence-account, openai-api-key, slack-workspace, uv
  • Docker
  • env example file
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#847 out of 100

react-agent

Minimal Python LangGraph ReAct agent with Tavily, ready for Studio

852 stars, MIT, last commit Oct 2026

A single-graph Python template: a ReAct loop in src/react_agent/graph.py that reasons, calls Tavily search, observes and repeats, with the model set by a provider/model-name string (default claude-sonnet-4-5-20250929, OpenAI as the alternative). Prompts, tools and runtime context are each one file; it opens in LangGraph Studio and deploys to LangGraph Platform. For Python developers who want the smallest LangGraph agent to extend.

Strengths

  • Three files to change: tools.py, prompts.py, graph.py
  • Model switch is a provider/model string in runtime context
  • Unit tests in CI; Studio hot reload and time travel work out of the box

Weaknesses

  • Only one tool (Tavily) and no UI; the chat surface is Studio
  • No persistence configuration beyond what LangGraph Platform provides
  • README still mentions Claude 3 Sonnet in one place; check defaults
  • Python, langgraph, anthropic, openai
  • Needs anthropic-or-openai-api-key, tavily-api-key, langgraph-cli
  • GitHub template
  • env example file
Repository on GitHub ↗ (opens in a new tab)
#945 out of 100

azure-ai-travel-agents

Travel-agency multi-agent sample using MCP servers in four languages

483 stars, MIT, last commit Sep 2026

Reference app where agents extract customer preferences, recommend destinations and plan itineraries, calling tools exposed as MCP servers written in Python, Node.js, Java and .NET. Three interchangeable orchestrators are provided: LangChain.js, LlamaIndex.TS and Microsoft Agent Framework (Python). It runs locally with Docker Model Runner and Phi4 14B, or deploys to Azure Container Apps with `azd up`.

Strengths

  • Three orchestrators (LangChain.js, LlamaIndex.TS, Microsoft Agent Framework) over the same MCP tools
  • MCP server examples in Python, Node.js, Java and .NET
  • OpenTelemetry tracing viewable in Aspire Dashboard
  • One-command Azure deploy with `azd up`; MIT license

Weaknesses

  • Sample app, not a reusable framework; the domain is fixed to travel
  • Local preview needs Phi4 14B (about 7.8 GB download, 16 GB RAM minimum)
  • Local GPU acceleration only on Apple Silicon and NVIDIA GPUs on Windows
  • Deployment path is tied to Azure; no release published
  • TypeScript, Phi4 14B (Docker Model Runner), Azure OpenAI, Microsoft Foundry
  • Needs Docker, Docker Model Runner, Node.js 22+, Azure Container Apps, Azure OpenAI or Microsoft Foundry
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#1044 out of 100

openai-cua-sample-app

Computer-use agent loops for Playwright browsers and PyAutoGUI desktops

1.9k stars, MIT, last commit Sep 2026

Two agent loops on the OpenAI Responses API where the model writes code against a persistent runtime: a TypeScript agent driving a browser through Playwright and a Python agent driving the real desktop through PyAutoGUI. A shared console on port 3000 runs scenarios against bundled lab apps and records screenshots and replay JSON. For developers building computer-use agents who want the loop, not a product.

Strengths

  • Lab apps and replay traces let you test the loop without touching real sites
  • Both agents share one console and contract types; tests in each app
  • Persistent execution worker pattern reduces model round trips

Weaknesses

  • No sandbox: generated code runs with your user permissions
  • Python agent controls your real mouse and keyboard
  • OpenAI-only; requires model access for computer use
  • Pinned Node 22.20.0 and pnpm 10.26.0
  • TypeScript, openai
  • Needs openai-api-key, playwright-chromium, uv
  • env example file
Repository on GitHub ↗ (opens in a new tab)
#1144 out of 100

data-enrichment

LangGraph agent that researches the web to fill your JSON schema

258 stars, MIT, last commit Oct 2026

A Python LangGraph graph that takes a research topic and a JSON extraction_schema, searches with Tavily, reads pages, fills the schema and checks the result for completeness before returning. The model is a provider/model string (default claude-3-5-sonnet-20240620, OpenAI supported), and it runs in LangGraph Studio or through the LangGraph API. For teams building lead or dataset enrichment pipelines.

Strengths

  • Schema-driven output: change the JSON schema, not the code, to extract different fields
  • Includes a validation step before returning results
  • Unit tests in CI; opens in Studio

Weaknesses

  • Default model string is dated (claude-3-5-sonnet-20240620)
  • Tavily is the only search tool
  • No batch runner; one topic per invocation
  • No UI beyond Studio
  • Jupyter Notebook, langgraph, anthropic, openai
  • Needs anthropic-or-openai-api-key, tavily-api-key, langgraph-cli
  • GitHub template
  • env example file
Repository on GitHub ↗ (opens in a new tab)
#1243 out of 100

agents-starter

Cloudflare Agents SDK chat starter with Durable Object state and scheduling

1.3k stars, MIT, last commit Jul 2026

A chat agent on Cloudflare Workers using the Agents SDK AIChatAgent class: streaming via Workers AI by default, three tool patterns (server auto-execute, client-side, human approval), one-off and cron scheduling, image input and a Kumo React UI. Messages persist in Durable Object SQLite, streams resume on reconnect, and swapping to OpenAI or Anthropic is an AI SDK provider import. For teams deploying agents on Cloudflare.

Strengths

  • No model API key needed; Workers AI is the default
  • Approval, client-side and server tools shown side by side in server.ts
  • Built-in scheduling, MCP client and state sync from the Agents SDK
  • npm run deploy ships to workers.dev

Weaknesses

  • Local dev still needs a Cloudflare login; Workers AI has no local simulator
  • Demo tools return fake data (getWeather is random)
  • No auth, no tests
  • State model is Durable Objects; not portable off Cloudflare
  • TypeScript, workers-ai, ai-sdk, openai, anthropic
  • Needs cloudflare-account, wrangler
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#1342 out of 100

react-agent-js

TypeScript createAgent starter with example tools and middleware hooks

118 stars, MIT, last commit Oct 2026

Four TypeScript files: agent.ts builds a LangChain createAgent, tools.ts defines calculator, time, weather and knowledge-search tools, prompts.ts holds the system prompt and index.ts is a CLI runner. Middleware for summarization and human-in-the-loop is shown but not wired, the model is a string like anthropic:claude-sonnet-4-5-20250929, and it opens in LangSmith Studio. For TypeScript developers starting a LangChain v1 agent.

Strengths

  • Tool definition pattern with Zod is the one you will reuse
  • Shows summarization and human-in-the-loop middleware in code
  • Model switch is a single string

Weaknesses

  • Example tools are stubs; no real integrations
  • No tests, no UI, no persistence
  • Seed shows 117 stars; small community
  • TypeScript, langchain, langgraph, anthropic, openai
  • Needs anthropic-or-openai-api-key
  • GitHub template
  • env example file
Repository on GitHub ↗ (opens in a new tab)
#1441 out of 100

new-langgraphjs-project

Empty TypeScript LangGraph.js scaffold with message history and tests

75 stars, MIT, last commit Oct 2026

The TypeScript counterpart of the blank LangGraph template: src/agent/graph.ts keeps a message history and returns a placeholder reply, with langgraph.json, .env.example and unit plus integration test workflows. It runs with npx @langchain/langgraph-cli dev and needs no API keys until you add a model. For TypeScript developers who want the LangGraph Platform layout without an opinionated agent.

Strengths

  • Runs with zero secrets; add a model when ready
  • Unit and integration test workflows included
  • Studio-ready langgraph.json

Weaknesses

  • Returns a placeholder until you add an LLM call
  • No UI, no tools
  • Seed shows 75 stars; the Python twin sees more activity
  • TypeScript, langgraph
  • Needs langgraph-cli
  • GitHub template
  • env example file
Repository on GitHub ↗ (opens in a new tab)
#1535 out of 100

agent-starter-pack

Google Cloud agent scaffolder with Terraform, CI/CD and evals; now maintenance-only

6.6k stars, Apache-2.0, last commit May 2026

A CLI (uvx agent-starter-pack create) that generates a Google Cloud agent project from six templates (ADK ReAct, ADK with A2A, agentic RAG on Vertex AI Search, LangGraph, ADK Java, ADK Live) with Terraform, Cloud Build or GitHub Actions pipelines, evaluation and observability, deploying to Cloud Run or Agent Engine. The README declares maintenance mode and points new work to agents-cli. For teams that need the generated infra and accept the migration.

Strengths

  • Generated project includes Terraform, CI/CD for all environments and an eval harness
  • enhance command retrofits deployment infra onto an existing agent
  • Documentation site plus a GEMINI.md context file

Weaknesses

  • Maintenance mode: critical fixes only, no new templates; README points to agents-cli
  • Google Cloud only; needs gcloud SDK, Terraform and Make
  • A generator, not a repo you fork directly
  • Last commit 2026-05
  • Python, google, google-adk, langgraph
  • Needs google-cloud-project, gcloud-sdk, terraform, make
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#1633 out of 100

new-langgraph-project

Blank Python LangGraph scaffold with config, tests and Studio support

297 stars, MIT, last commit Oct 2026

The blank-slate LangGraph template: src/agent/graph.py holds a one-node graph that returns a fixed string and its runtime context, with langgraph.json, a .env.example and unit plus integration test workflows already in place. Start it with langgraph dev and open it in Studio; there is no model, no tools and no UI. For Python developers who want the LangGraph Platform layout without an opinionated agent.

Strengths

  • Correct langgraph.json, package layout and CI from the first commit
  • No model dependency; add the provider you want
  • Unit and integration test workflows included

Weaknesses

  • Does nothing until you add a model call and nodes
  • No chat UI; Studio or the API is the interface
  • Assumes LangGraph Server and Platform as the runtime
  • Python, langgraph
  • Needs langgraph-cli
  • env example file
Repository on GitHub ↗ (opens in a new tab)
#1726 out of 100

claude-managed-agents

Self-hosted control plane running Claude Managed Agents on Cloudflare Workers

325 stars, MIT, last commit May 2026

A Cloudflare Workers control plane that receives Claude Managed Agents webhooks and starts a sandbox per session, either a Cloudflare Container or an Isolate sandbox. It adds egress policies with credential injection, Workers VPC access to private services, and built-in tools for email, browser automation and image generation. A dashboard and API are deployed to your own account. The README labels it alpha software meant as a starting point to fork.

Strengths

  • Two sandbox backends: full containers or lightweight isolates, chosen per agent
  • Egress policies inject credentials so the agent never sees secrets
  • Custom tools declared in one file with direct access to Worker bindings
  • Private services reachable through Workers VPC without public exposure

Weaknesses

  • README calls it alpha software: not stable, may contain bugs
  • Requires a paid Cloudflare Workers plan or Enterprise account
  • Dashboard is unsecured by default until Cloudflare Access is configured
  • Tied to Claude Managed Agents and Anthropic keys; no other model providers
  • TypeScript, Claude (Anthropic)
  • Needs Cloudflare Workers Paid plan, Cloudflare D1, Cloudflare KV, Cloudflare R2, Durable Objects, Anthropic API, Docker (terminal deploy)
  • Docker
Repository on GitHub ↗ (opens in a new tab)
#1821 out of 100

openai-cs-agents-demo

Airline support multi-agent demo with visible handoffs and guardrails

6.6k stars, MIT, last commit Dec 2025

A Python backend on the OpenAI Agents SDK that routes airline support requests between six agents (triage, flight info, booking, seats, FAQ, refunds) with relevance and jailbreak guardrails, plus a Next.js UI on ChatKit that shows each handoff and guardrail trip as it happens. Data is mock itineraries, tools are in-process functions, and there is no auth or persistence. For teams evaluating the Agents SDK handoff pattern.

Strengths

  • Orchestration view makes handoffs and guardrail trips visible per message
  • Six agents and two guardrails in one readable backend
  • npm run dev starts both UI (3000) and backend (8000)

Weaknesses

  • Demo data only; mock flights and bookings
  • No auth, persistence, tests or Docker
  • OpenAI Agents SDK and ChatKit only
  • Last commit 2025-12
  • Python, openai, openai-agents-sdk, chatkit
  • Needs openai-api-key
Repository on GitHub ↗ (opens in a new tab)

Written from each project's README and checked facts. Spot something wrong? Report it on GitHub (opens in a new tab).