MCP server

Labelixa Official

com.labelixa/zpl

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Thermal label MCP server: render, validate, debug and convert ZPL, EPL, TSPL and CPCL labels.

Website Source

At a glance

Type

MCP server

Publisher

labelixa.com (verified by the MCP Registry)

Status

Working at last check

Tools

23

Token cost

About 4,437 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http zpl https://api.labelixa.com/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.zpl]
url = "https://api.labelixa.com/mcp"

Gemini CLI

{"mcpServers":{"zpl":{"httpUrl":"https://api.labelixa.com/mcp"}}}

Cursor

{"mcpServers":{"zpl":{"url":"https://api.labelixa.com/mcp"}}}

VS Code

{"servers":{"zpl":{"type":"http","url":"https://api.labelixa.com/mcp"}}}

Antigravity

agy mcp add zpl https://api.labelixa.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"zpl","server_url":"https://api.labelixa.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"zpl","server_url":"https://api.labelixa.com/mcp"}

Tools

• barcode_png ~132 tokens
  Generate a single barcode as a PNG image (Code 128, QR, DataMatrix, EAN-13, UPC-A, PDF417 and more). For a full label with text and layout, write ZPL and use zpl_preview instead.
• barcode_verify ~160 tokens
  Decode barcodes from a photo or scan of a PRINTED label (PNG, JPEG, BMP or GIF) and report what a software decoder reads back. Honest by design: 'read' does not guarantee every handheld scanner will read it, and 'not read' does not condemn the label (photo angle/focus matter) — the response says so.
• bulk_list ~89 tokens
  List your recent bulk jobs (id, state, error class, timestamps), newest first. Useful to recover a lost job id; details via bulk_status.
• bulk_status ~144 tokens
  Status of one bulk job you own: state, attempt count and — when finished — the summary with produced count and per-row failures (row number + reason; failed rows never block the rest). Finished outputs stay downloadable for 7 days via the REST endpoint the response names.
• bulk_submit ~318 tokens
  Submit a bulk label production job: one ZPL template with {{variable}} placeholders plus data rows (one object per label). Requires an API key whose plan includes bulk jobs. Quota is charged UPFRONT, one operation per row, and failed rows are not refunded; rows per job are capped by plan. Returns th
• convert_zpl_dpi ~203 tokens
  Rescale ZPL between printer resolutions (203/300/600 DPI): coordinates, fonts, barcode module width and label size are scaled. Embedded ^GF/~DG image data is NOT scaled; the response says so instead of silently passing it through.
• cpcl_preview ~171 tokens
  Render CPCL label code and return a PNG preview. The preview assumes 203 dpi and is an interpretation of the CPCL manual covering a core command subset — no physical printer validation. `labels` in the response is the TOTAL number of labels the stream prints (a stream may contain several, each ended
• cpcl_validate ~139 tokens
  Lint CPCL label code and return positioned findings with severity as JSON. Checks the command set Labelixa implements from the CPCL manual — a clean result is not a guarantee that a specific printer accepts the job. Run this before cpcl_preview; if you are not sure which language the code is, call l
• epl_preview ~171 tokens
  Render EPL/EPL2 label code and return a PNG preview. The preview assumes 203 dpi and is an interpretation of the EPL2 manual covering a core command subset — no physical printer validation. `labels` in the response is the TOTAL number of labels the stream prints (a stream may contain several, each e
• epl_validate ~140 tokens
  Lint EPL/EPL2 label code and return positioned findings with severity as JSON. Checks the command set Labelixa implements from the EPL2 manual — a clean result is not a guarantee that a specific printer accepts the job. Run this before epl_preview; if you are not sure which language the code is, cal
• explain_zpl ~261 tokens
  Human-readable health REPORT for a finished ZPL label, with a 0-100 score: sectioned findings (syntax, size/DPI, orientation, barcodes, fonts, graphics memory, job behaviour); sections that cannot be assessed say so and are excluded from the score. Use it to review or explain a label to a person; fo
• image_to_zpl ~224 tokens
  Convert an image (PNG, JPEG, BMP or GIF, max 200 KB) to a ZPL ^GF graphic command. Returns the ZPL plus measured dimensions and the physical print size at the chosen density. PDF input is REST-only (/v1/graphics).
• language_detect ~107 tokens
  Detect which printer language raw label code is written in (ZPL, EPL, TSPL or CPCL). Heuristic: returns the language plus a confidence TIER (high/medium/low) and signal codes — not a probability.
• printer_language_to_zpl ~431 tokens
  Convert a SATO SBPL, Honeywell (Datamax) DPL or Honeywell (Intermec) IPL label stream to ZPL, so it can be checked with zpl_validate and rendered with zpl_preview. You must name the source language: language_detect does not recognise these three. Real control characters and the manuals' readable not
• save_label ~258 tokens
  Save a ZPL label to a Labelixa account so it can be edited, versioned and printed later. With an API key the label is saved immediately and the saved label id is returned. Without a key the label is held for 24 hours and a one-time link is returned: the user opens it, signs in (free account is enoug
• template_get ~148 tokens
  Fetch one catalog template: metadata, preview image URL and — for non-premium templates — the ZPL source, ready for zpl_preview. Premium templates return metadata for everyone; their ZPL source requires an API key whose plan includes the premium-template feature (same rule as the website).
• template_list ~138 tokens
  List Labelixa's first-party label template catalog: id, English name, category, size/density and tags. Read-only product content (no tenant data). Fetch one with template_get; render its ZPL with zpl_preview.
• tspl_preview ~174 tokens
  Render TSPL/TSPL2 label code and return a PNG preview. The preview assumes 203 dpi and is an interpretation of the TSPL manual covering a core command subset — no physical printer validation. `labels` in the response is the TOTAL number of labels the stream prints (a stream may contain several, each
• tspl_validate ~143 tokens
  Lint TSPL/TSPL2 label code and return positioned findings with severity as JSON. Checks the command set Labelixa implements from the TSPL2 manual — a clean result is not a guarantee that a specific printer accepts the job. Run this before tspl_preview; if you are not sure which language the code is,
• zpl_command_help ~182 tokens
  Explain a single ZPL command: syntax, parameters with types/ranges/options, a fragment example and whether the Labelixa renderer draws it. Data comes from the same catalog that powers the public command reference pages.
• zpl_compatibility ~149 tokens
  Compatibility RISK analysis of ZPL code against a specific printer model, given as manufacturer/model (e.g. 'zebra/zd421'). NOT an emulator and never says 'it works': reports the model's language posture with evidence level and size-rule findings.
• zpl_preview ~274 tokens
  Render ZPL label code and return the label as a PNG image. Use this to SEE what ZPL output looks like — LLMs can write ZPL but cannot otherwise verify the visual result. One call renders one label (use `index` to pick a label from a multi-label stream). The result also carries an 'Open this label in
• zpl_validate ~281 tokens
  Pass/fail lint for ZPL — machine-readable diagnostics with line/column, code and severity: unknown commands, missing ^FS, out-of-range parameters, fields outside the label. Fast; run it before zpl_preview whenever you generate or edit ZPL. For a human-readable report with a score, use explain_zpl in

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