smolanalytics: analytics you ask from your editor, answers CI-tested to match the dashboard
LocalAbout smolanalytics: analytics you ask from your editor, answers CI-tested to match the dashboard
smolanalytics runs natural-language end-to-end tests in a real browser and replays tests that have passed. It is for developers checking web behavior from an editor or CI; its MCP tools run tests and report whether a release can ship.
Key features
- 01Describe end-to-end tests in one sentence
- 02Run tests in a real browser
- 03Record and replay passing tests
- 04Distinguish failed, stale, errored, and flaky results
- 05Post test reports on pull requests
Use cases
- 01Check that a pricing page shows a monthly price
- 02Run a test suite on each pull request
- 03Inspect tests and release status from an editor
MCP support
It provides three MCP tools—`run_tests`, `can_i_ship`, and `list_tests`—for editor clients to run tests, inspect the test list, and check release status.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y smolanalyticsANTHROPIC_API_KEYSecretYour own Claude key. run_tests needs it for a test with no recording yet; a replay needs none.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
3Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| url | string | Yes | Where the app is running, e.g. http://localhost:3000 |
| since | string | No | Optional git ref: run only the tests this change could have broken, e.g. 'main' |
| suite | string | No | Folder of .md test files (default: tests/) |
| maxCalls | number | No | Ceiling on model calls for this run. 0 means no ceiling. |
Details
From the project READMEsmolanalytics
End-to-end tests written as one English sentence. An agent runs them in a real browser, and a passing run replays with no model call.
npx smolanalytics test --url https://yourapp.com --test "the pricing page shows a monthly price"
A test is one sentence in a markdown file. An agent opens a real browser, reads the page through its accessibility tree, works out how to do what the sentence says, and returns a verdict. There is no test code, so there is no selector to update when a button moves.
A run that passes is recorded, and every run after it replays that recording with no model call at all. The agent comes back only when the recording stops fitting your app.
Five verdicts, never blurred: passed, failed, stale, errored, flaky. Only failed is a claim about your app. A recording that stopped fitting is stale, never a bug report, and a runner that could not finish is errored, never counted against you.
On every pull request
test --suite tests/ --url <preview> --comment runs a folder of sentences and leaves one comment on
the pull request, edited in place on every push: what broke, the file most likely responsible and
the evidence for that guess. Exit codes are 0 (clean), 1 (your app failed a test) and 2 (the runner
could not finish). The workflow file is in the docs.
In your editor (MCP)
{ "mcpServers": { "smolanalytics": { "command": "npx", "args": ["-y", "smolanalytics", "mcp"] } } }
Three tools: run_tests, can_i_ship and list_tests. Listed on the official MCP Registry as
io.github.Arjun0606/smolanalytics.
Evidence rather than claims
smolanalytics.com/proof is a GitHub Action that runs this product's own suite against two live sites every night and publishes every verdict, including the red ones. Nothing on that page is written by hand.
What it costs
The CLI runs on your machine or your CI runner, on your own ANTHROPIC_API_KEY. A first run of a
test costs roughly what one agent conversation costs; a replay costs nothing. The hosted side at
smolanalytics.com is $19/month with 100 tested pull requests included,
after a 14-day trial with no card. This is commercial software, not open source.
Full CLI reference: cli/README.md. Questions: smolanalytics.com/contact.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.