mcp-server-caniemail

MCP server giving an AI agent email client HTML/CSS compatibility data, backed by caniemail.com.

Email clients are not browsers. Outlook on Windows renders with Microsoft Word, support for anything modern is patchy, and the difference between "works with a workaround" and "nobody has ever tested this" decides whether an email ships broken.

Install

{
  "mcpServers": {
    "caniemail": {
      "command": "npx",
      "args": ["-y", "mcp-server-caniemail"]
    }
  }
}

Node 22+. Set CANIEMAIL_OFFLINE=1 to skip the network and use the bundled dataset.

Tools

• lint_email takes drafted HTML and/or CSS plus a client list, and returns only what breaks, with every source position the feature was used at, affected clients, documented workarounds, and a feature URL. Passing features are never returned.
• check_feature_support gives per-client verdicts for one feature, for deciding how to build something rather than checking what you built.
• search_features finds feature slugs by keyword. Slugs are not guessable: "rounded corners" is css-border-radius, flexbox is css-display-flex.
• list_email_clients is the roster of 48 clients with display names. It is inlined into the other tools' descriptions, so this is rarely needed.

Four verdicts, not a boolean

| Verdict | Severity | Meaning | |---|---|---| | supported | none | Use it. | | unsupported | error | Will not render. Use a fallback. | | mitigated | warning | Works with a documented workaround. The note is the answer. | | untested | unknown | No data. Not evidence of support, or against it. |

Around a sixth of the matrix is untested. Results also carry last_test_date and a staleness note, because some entries have not been retested in five years.

Data is fetched from caniemail.com and cached for 24 hours; every result names which copy answered via data_source. The server revalidates as it runs rather than loading once at startup, so a session left open for days does not keep answering from the copy it fetched on the first morning. Startup itself touches no network, so the handshake never waits on caniemail.com.

lint_email is sized for an agent's context. A finding carries only what its verdict decides, meaning the severity, the clients affected and the notes. Everything that does not vary by verdict is stated once in a features legend keyed by slug: the title, the URL, the last test date, and positions, which lists every place the markup uses the feature as "line:col-line:col" strings with an occurrence_count. clients_affected is compressed against the clients you asked for, so "*" or "outlook.*", with client_count always exact. The per-severity advice is a second legend, guidance, rather than a paragraph repeated on every finding.

Scope

Rendering only. Nothing about deliverability, SPF/DKIM/DMARC/BIMI, list management, or choosing between ESPs.

License

MIT. The caniemail dataset is a separate work, MIT, © 2019 Rémi Parmentier, fetched at runtime rather than redistributed here.

Source: https://github.com/shbernal/caniemail-ai-tooling