
E2e Runner
io.github.fastslackPublished by GitHub account fastslackv1.3.0Updated Oct 24, 2026
JSON-driven E2E test runner with parallel Chrome pool execution and 16 MCP tools.
Overview
Lets an assistant write, run, and debug JSON-based end-to-end browser tests against a web app, with screenshots and network logs.
- What you can do
- E2E Runner exposes MCP tools for running test suites, listing suites, creating test and module JSON files, capturing screenshots of any URL, analyzing page structure, and querying run history, network logs, and stability insights. Tests are plain JSON action lists executed in a real browser pool, with pass/fail, timing, screenshots, and network errors reported back. It also fetches GitHub or GitLab issues and generates tests from them, and offers a web dashboard for live runs and history.
- When to use it
- Use it when you want an assistant to create and execute browser end-to-end tests for a web app without writing test code, verify whether a reported bug reproduces, or capture and inspect pages during development. It fits teams that already run a local app and want test creation, execution, and reporting in one conversation.
- Requirements
- Local process via npx or Docker; Node.js 20 or newer. A reachable browser endpoint is needed: an existing Chromium launched with a remote debugging port, the Obscura binary, or Docker for the parallel Chrome pool. GitHub issue features need the gh CLI and GitLab features the glab CLI. No API key is required for visual verification.
Installation
In SourceWeft
- Open E2e Runner in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
English · Español
@matware/e2e-runner
The AI-native E2E test runner that writes, runs, and debugs tests for you.
[npm version] [node version] [npm downloads] [Docker pulls] [GitHub stars] [license] [MCP compatible] [AI native] [OpenCode compatible] [Agent Skills]
E2E Runner lets you test your web app without writing test code. Tests are plain JSON — and you don't even have to write that yourself: just ask Claude Code.
🎬 Write a test by asking — then watch it run
[Live dashboard streaming screenshots as a test suite runs]
The live dashboard while a suite runs — every step streams a screenshot into the feed, in real time.
With the built-in MCP server, creating a test is a conversation — no docs, no syntax to memorize:
You: Create an E2E test for the login flow and run it.
Claude Code: writes the test, runs it in a real browser, and reports back — ✅
login-flowpassed in 2.3s · screenshot saved · no network errors.
Behind the scenes Claude just wrote and ran this. A test is just JSON — an ordered list of what a user does:
No imports, no describe/it, no build step. If you can read it you can write it — or just ask.
Connect it to Claude Code (2 commands):
Now say "create a test for X and run it" — Claude gets 17 MCP tools, slash commands, and specialized agents.
Using a different agent (Cursor, Codex, Copilot, 40+ more)? Install the skill:
npx skills add fastslack/mtw-e2e-runner
📖 Contents
🚀 Install — it's tiny
Then pick how to run the browser. You don't need Docker unless you want the parallel pool:
Option 1 · Use the Chrome you already have — no Docker ⭐
Launch any Chromium browser with a debugging port, then point the runner at it:
Or bake it into e2e.config.js so you never repeat it:
Nothing to install beyond npm, and baseUrl is just localhost (the browser is on your machine).
Option 2 · Obscura — one tiny binary, no Docker
A single ~30 MB binary with built-in anti-detection. Install once, run it, point the runner at it:
npx e2e-runner pool start (with poolDriver: 'obscura' in your config) prints the exact install command for your OS.
Option 3 · Docker pool — parallel, for CI & big suites
A shared, queue-managed Chrome pool that runs many tests at once:
Requires Docker. Set baseUrl: 'http://host.docker.internal:3000' so the containerized Chrome can reach your app.
Why host.docker.internal (Docker option only)?
With the Docker pool, Chrome runs inside a container, so localhost there means the container — not your machine. host.docker.internal bridges to your host. On Linux (Docker Engine, not Docker Desktop) add --add-host=host.docker.internal:host-gateway, or use your LAN IP. Options 1 & 2 don't have this — the browser is local, so plain localhost just works.
Write your first test
Open e2e/tests/sample.json — a flow is an ordered list of actions:
Run it with npx e2e-runner run --all. Results — pass/fail, timing, screenshots, network errors — print to your terminal and to the web dashboard if it's open.
Updating
Each install method updates separately — bump the one(s) you use:
[!NOTE] Two gotchas: (1)
npxprefers a copy found in the project'snode_modulesover its own cache — if a project pins an old version, the MCP server and dashboard run that old version, so update the project dependency too. (2) Already-running processes keep the old code in memory: after updating, restart the dashboard and reconnect the MCP server (/mcp→e2e-runner→ Reconnect, or restart your session).
✨ What you get
🧪 Zero-code tests — JSON files that anyone on your team can read and write. No JavaScript, no compilation, no framework lock-in.
🤖 AI-powered testing — Claude Code creates, executes, and debugs tests natively through 17 MCP tools. Ask it to "test the checkout flow" and it builds the JSON, runs it, and reports back.
🐛 Issue-to-Test pipeline — Paste a GitHub or GitLab issue URL. The runner fetches it, generates E2E tests, runs them, and tells you: bug confirmed or not reproducible.
👁️ Visual verification — Describe what the page should look like in plain English. The AI captures a screenshot and judges pass/fail against your description. No pixel-diffing setup needed.
🧠 Learning system — Tracks test stability across runs. Detects flaky tests, unstable selectors, slow APIs, and error patterns — then surfaces actionable insights.
⚡ Parallel execution — Run N tests simultaneously against a shared browser pool (browserless, raw CDP, Lightpanda, Obscura, or Steel). Serial mode available for tests that share state.
🎯 Pluggable browser drivers — Pick the engine that fits each test: real Chrome via browserless, Lightpanda or Obscura for fast lightweight runs, Steel for managed sessions. Set driver per test or override the whole run with --driver.
📊 Real-time dashboard — Live execution view, run history with pass-rate charts, screenshot gallery with hash-based search, expandable network request logs.
🔁 Smart retries — Test-level and action-level retries with configurable delays. Flaky tests are detected and flagged automatically.
📦 Reusable modules — Extract common flows (login, navigation, setup) into parameterized modules and reference them with $use.
🏗️ CI-ready — JUnit XML output, exit code 1 on failure, auto-captured error screenshots. Drop-in GitHub Actions example included.
🌐 Multi-project — One dashboard aggregates test results from all your projects. One Chrome pool serves them all.
🐳 Portable — Chrome runs in Docker, tests are JSON files in your repo. Works on any machine with Node.js and Docker.
✍️ Writing tests
Everything about authoring tests — the file format, the full action vocabulary, retries, state isolation, and reuse. Expand what you need:
Test format & file layout
Each .json file in e2e/tests/ contains an array of tests. Each test has a name and sequential actions:
Suite files can have numeric prefixes for ordering (01-auth.json, 02-dashboard.json). The --suite flag matches with or without the prefix, so --suite auth finds 01-auth.json.
Action catalog — navigation, input & interaction
Click by text — when click uses text instead of selector, it searches across common interactive and content elements:
Assertions — verify text, elements, URLs, counts & network
Framework-aware actions — React/MUI without evaluate boilerplate
These actions handle common patterns in React/MUI apps that normally require verbose evaluate boilerplate:
Multi-tab actions — popups, OAuth windows & cross-tab flows
All subsequent actions run in the active tab:
Retries & flaky detection
Test-level retry — retry an entire test on failure. Set globally via config or per-test:
Tests that pass after retry are flagged as flaky in the report and learning system.
Action-level retry — retry a single action without rerunning the entire test. Useful for timing-sensitive clicks and waits:
Set globally: actionRetries in config, --action-retries <n> CLI, or ACTION_RETRIES env var. Delay between retries: actionRetryDelay (default 500ms).
Serial tests — for tests that share state
Tests that share state (e.g., two tests modifying the same record) can race when running in parallel. Mark them as serial:
Serial tests run one at a time after all parallel tests finish — preventing interference without slowing down independent tests.
Testing authenticated apps
The simplest approach — log in via the UI like a real user:
For SPAs with JWT, skip the login form by injecting the token directly:
Or set it globally in config:
Each test runs in a fresh browser context, so auth state is automatically clean between tests.
More strategies: Cookie-based auth, HTTP header injection, OAuth/SSO bypasses, reusable auth modules, and role-based testing — see docs/authentication.md
Reusable modules — extract common flows with $use
Extract common flows into parameterized modules:
Use in tests:
Modules support parameter validation (required params fail fast), conditional blocks ({{#param}}...{{/param}}), nested composition, and cycle detection.
Hooks — beforeAll / beforeEach / afterEach / afterAll
Run actions at lifecycle points. Define globally in config or per-suite:
Important:
beforeAllruns on a separate browser page that is closed before tests start. UsebeforeEachfor state that tests need (cookies, localStorage, auth tokens).
Exclude patterns — skip drafts from --all
Skip exploratory or draft tests from --all runs:
Individual suite runs (--suite) are not affected by exclude patterns.
🤖 AI integration
The whole point: your agent writes, runs, and verifies tests for you.
Claude Code — plugin install & MCP-only install
This gives Claude 17 MCP tools, a workflow skill, 4 slash commands (/e2e-runner:run, /e2e-runner:create-test, /e2e-runner:verify-issue, /e2e-runner:capture), and 3 specialized agents (test-analyzer, test-creator, test-improver).
MCP-only install (tools only, no skill/commands/agents):
The 17 MCP tools
Pool start/stop are CLI-only — not exposed via MCP.
Visual verification — describe the page, AI judges it
Describe what the page should look like — AI judges pass/fail from screenshots:
After test actions complete, the runner auto-captures a verification screenshot. The MCP response includes the screenshot hash — Claude Code retrieves it and visually verifies against your expect description. No API key required.
Issue-to-test — turn a bug report into a runnable test
Turn GitHub and GitLab issues into executable E2E tests. Paste an issue URL and get runnable tests — automatically.
How it works:
- Fetch — Pulls issue details (title, body, labels) via
ghorglabCLI - Generate — AI creates JSON test actions based on the issue description
- Run — Optionally executes the tests immediately to verify if a bug is reproducible
In Claude Code, just ask:
"Fetch issue #42 and create E2E tests for it"
Bug verification logic: Generated tests assert the correct behavior. Test failure = bug confirmed. All tests pass = not reproducible.
Auth: GitHub requires gh CLI, GitLab requires glab CLI. Self-hosted GitLab is supported.
📊 Dashboard & insights
Web dashboard tour — live view, history, gallery, pool status
Live execution — monitor tests in real-time with step-by-step progress, durations, and active worker count.
[Dashboard - Live test execution]
Test suites — browse all suites across projects. Run a single suite or all tests with one click.
[Dashboard - Test suites grid]
Run history — track pass-rate trends with the built-in chart. Click any row to expand full detail.
Run detail — PASS/FAIL badges, screenshot thumbnails with copyable hashes (ss:77c28b5a), formatted console errors, and network request logs.
Screenshot gallery — browse all captured screenshots with hash search (action, error, and verification captures).
[Dashboard - Screenshot gallery]
Pool status — Chrome pool health: available slots, running sessions, memory pressure.
Learning system — flaky tests, unstable selectors, slow APIs
The runner learns from every test run — building knowledge about your test suite over time. Query insights via the e2e_learnings MCP tool:
Storage & export:
- SQLite (
~/.e2e-runner/dashboard.db) — default, zero setup - Neo4j knowledge graph — optional, for relationship-based analysis. Manage via
e2e_neo4jMCP tool ordocker compose - Markdown report (
e2e/learnings.md) — auto-generated after each run
Test narration: Each test run generates a human-readable narrative of what happened step by step, visible in the CLI output and the dashboard.
Network error handling — assertions, global flag, full logging
Explicit assertion — place assert_no_network_errors after critical page loads:
Global flag — set failOnNetworkError: true to automatically fail any test with network errors:
When disabled (default), the runner still collects and reports network errors — the MCP response includes a warning when tests pass but have network errors.
Full network logging — all XHR/fetch requests are captured with URL, method, status, duration, request/response headers, and response body (truncated at 50KB). Viewable in the dashboard with expandable request detail rows.
MCP drill-down flow:
The e2e_run response stays compact (~5KB) regardless of how many requests were captured. Use e2e_network_logs with the returned runDbId to drill into details on demand.
Screenshot capture — snapshot any URL on demand
Capture screenshots of any URL on demand — no test suite required:
Via MCP, the e2e_capture tool supports authToken and authStorageKey for authenticated pages — it injects the token into localStorage before navigating.
Every screenshot gets a deterministic hash (ss:a3f2b1c9). Use e2e_screenshot to retrieve any screenshot by hash — it returns the image with metadata (test name, step, type).
🌐 Browser drivers
The runner can talk to multiple browser engines through different drivers. The default is auto — it probes each pool URL and picks the right driver per pool.
Pick a driver per test / force one per run
driver is optional. If set, only pools whose detected driver matches become candidates. fallbackDriver is explicit opt-in — without it, a missing target driver fails the test with a clear message. Pool busyness does not trigger fallback; the runner waits inside the filtered set.
Force a driver for a whole run (CLI overrides win over per-test fields — useful for A/B benchmarks):
Running each driver locally
⚙️ CLI, config & CI
CLI commands
CLI options
Configuration — e2e.config.js & priority
Create e2e.config.js in your project root:
Config priority (highest wins):
- CLI flags
- Environment variables
- Config file (
e2e.config.jsore2e.config.json) - Defaults
When --env <name> is set, the matching profile overrides everything.
CI/CD — JUnit XML & GitHub Actions
Programmatic API
Requirements
- Node.js >= 20
- Docker — only for Option 3 (the parallel Chrome pool). Options 1 & 2 don't need it.
License
Copyright 2026 Matias Aguirre (fastslack) — Matware
Licensed under the Apache License, Version 2.0. See LICENSE for details.
Source: README.md at commit 72b472f
Tools
0Version history
1- v1.3.0LatestSep 16, 2026
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