tabnas

Seven tools over the tabnas parsing engine: parse, validate, diagnose, fixtures, compare.

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What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    Seven tools over the tabnas parsing engine: parse, validate, diagnose, fixtures, compare.

    How to connect

    How to connect tabnas to Claude

    The server address to paste into Claude settings:

    https://mcp.tabnas.dev/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect tabnas to ChatGPT

    The server address to paste into ChatGPT settings:

    https://mcp.tabnas.dev/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect tabnas to Cursor

    The server address to paste into Cursor settings:

    https://mcp.tabnas.dev/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (7)

    Raw names from tools/list. Only developers need these.

    parseParse input with the tabnas engine. Returns {ok:true, tree} or, on parse failure, {ok:false, diagnostic} — the structured diagnostic described by resource tabnas://schema/diagnostic. An invalid grammar is rejected as {ok:false, errors:[{path,message}]}. Without a grammar the bare engine is used, which defines no rules and produces an undefined tree for every input.
    validate_grammarValidate a serialized GrammarSpec. Structural validation against the bundled grammar schema, an engine load in a fresh instance, and a check that every rule reference (`p`, `r`) names a rule the grammar actually defines — a dangling reference loads cleanly and then fails at parse time with `unknown_rule`. Returns {ok:true, v} (v = declared builtin config-schema version, absent means 1) or {ok:false, errors:[{path,message}]}. Security: a grammar carrying a `ref` key, or any function reference that is not a $-suffixed engine builtin, is rejected — validating a grammar never runs supplied code.
    explain_parse_errorParse input and explain the failure. Returns {failed:false} when the input parses; otherwise {failed:true, diagnostic, registry} where registry is the error-code registry entry {code,message,hint} for the diagnostic code (resource tabnas://errors), or null for a code the bundled registry does not know (e.g. a plugin-declared code).
    test_grammarRun TSV fixture content against a grammar in a fresh instance, using the fleet fixture convention (@tabnas/support): line 1 is a header, the input column is escape-decoded, the expected column is JSON or ERROR / ERROR:<code>. Returns {pass, fail, rows:[{row,input,expected,got,ok}]}. Refuses more than 10000 rows.
    list_pluginsList every bundled tabnas plugin descriptor (tabnas.plugin.json of each fleet repo), sorted by name. Returns {plugins:[...]}.
    describe_pluginThe full descriptor for one plugin, by package name ('@tabnas/csv') or bare fleet name ('csv'). Unknown names get {ok:false, errors} naming the known plugins.
    compare_grammarsGrammar compatibility (AX plan Phase 5): does candidate grammar B still accept what baseline A accepted, and does it build the same tree for inputs both accept? Returns EVIDENCE AND CONFIDENCE, never a bare verdict: {normalForm, proven[], observed[], changes[], counterexamples[], confidence, why}. confidence:'low' with a stated reason is a successful run, not a failure — language inclusion is undecidable in general, so anything outside the decidable subset is reported not-proven rather than incompatible. Supply `corpus` (real inputs) for the tier that measures what your documents actually do.