ai-logo-maker

Turn a brand name, industry, or reference image into a professional AI logo, brand mark, or app icon. This AI logo maker and logo generator explores multiple design directions from your brand brief—company name, industry feel, and color preferences—then refines the strongest concept with precise brand colors, clean geometry, and scalable composition. Create business logos, startup logos, monograms, emblems, and combination marks that stay sharp from favicon to storefront sign. Start from a text description, transform existing sketches and brand assets into a polished mark, or refine an accepted draft toward a publish-ready result.

Create one focused logo or brand mark from a brand name, an industry cue, a set of visual references, or an accepted draft. Reuse decisions already present in the conversation and move by the shortest route that completes the requested mark.

Choose the route

• Create from a brand brief: when no source image exists, extract the brand name, industry feel, and one style direction, then use beatra.images.generate with a square canvas. Default to two concepts so the user can compare directions before committing.
• Compose from references: with one to four sketches, mood boards, or brand assets, preserve their declared order and use beatra.images.transform. A brand name or style note is needed only when it changes the composition.
• Refine an accepted draft: use beatra.images.edit with the draft as images[0]. The accepted draft and requested change are sufficient to begin.

Follow brand brief and routing for the precise branch and logo craft when turning the brief into a visual specification that scales.

Shape one brand brief

Reuse the user's brand name, industry, style preferences, color values, reference images, and intended use. Restate what is already known before asking. Enter a structured brief only when the request is just “make a logo” and those facts are missing. Ask only when a missing decision materially changes the result. For a standard logo or app icon, propose a square 1:1 canvas as the working master; otherwise prefer the user's stated dimensions or an accepted draft's existing ratio.

Build the brief around:

• the brand or project name that should appear in or accompany the mark;
• one industry or personality cue (tech, food, finance, playful, bold, minimal);
• one logo type preference when known—wordmark, lettermark, pictorial mark, abstract mark, monogram, emblem, or combination mark;
• exact brand colors when the user provides hex values;
• one intended primary use (app icon, website header, social avatar, print) when it changes the composition or safe-area needs.

If the user has already chosen the style or type, reuse it. If that choice is genuinely missing, propose the best default and include it in the single paid-call confirmation instead of creating a separate interview.

Follow this golden path: reuse context, lock the brand name and intended use, present one exploration confirmation that produces a limited set of variants, then refine only after the user names a direction.

Prepare the call

Use only this Skill's bundled scripts/mcp_client.py for every remote MCP operation. The tool name is a CLI argument and the tool arguments are the JSON sent on stdin. Do not configure or call a host Beatra Connector, and do not use REST/OpenAPI as a fallback. For exact commands and troubleshooting, use Bundled MCP Client diagnostics.

• With no source image, call beatra.images.generate with an explicit square 1:1 canvas and a prompt built from the brand brief. Default count to two so the user can compare; raise it to three or four only when the user asks for more options.
• With one to four ordered references, upload local files through the bundled client helpers, then call beatra.images.transform with an explicit canvas.
• For an accepted draft, call beatra.images.edit. Use at most two normalized edit_regions on image_index=0 for local work; omit regions for a whole-image adjustment.

When the user provides exact brand colors, encode them as a structured palette (three to ten weighted RGB entries whose weights sum to exactly 1.0000) rather than describing colors in prose. Keep model=auto and count at its default unless the user explicitly chooses otherwise. Call beatra.models.list only for a real model, availability, compatibility, or price decision. The detailed request shapes and examples are in workflow.

Uploading makes bytes available to the remote tool; it does not itself inspect the image. Review only visual facts the host can actually see.

Confirm and execute once

Planning and brief preparation are free. Before the paid image call, show and freeze the final prompt, ordered references, canvas, brand palette, logo type, model, controls, and output count. Merge any still-material high-impact choice into this one confirmation.

After approval, create one stable opaque client_request_id for that exact logical request and submit it once. A changed prompt, reference or order, canvas, palette, model, count, or control is new paid work and needs a new confirmation and a new ID.

Track, review, and deliver

After receiving a task_id, poll only that task with beatra.tasks.get. If the ID is lost, use beatra.tasks.list to find candidates and verify the selected one with tasks.get. Only when the original response status is genuinely unknown may the exact same parameters and same client_request_id be used for idempotent recovery. Slow polling, an update failure, an authorization failure, or a connection failure never creates a replacement paid task.

Use beatra.tasks.cancel only when the user asks. If cancellation returns 409, continue tracking the original task. See review and recovery for the full recovery contract.

When the result is visible, review scalability (is the mark still recognizable at thumbnail size?), brand-color accuracy, silhouette strength, safe-area margin, and whether a single-color version would hold up. Deliver the artifact links, observed dimensions, task ID, and billing.net_charged_credits. Offer at most one focused, unexecuted revision. When the primary use needs a different ratio or a dark-background variant, advise that it is a separate focused request. Generated assets can also be viewed and managed at beatra.ai.

References by task

• Choosing among generate, transform, and edit, or planning a logo type strategy: brand brief and routing
• Turning a brief into a scalable visual specification: see logo craft
• Exact request shapes, palette encoding, and JSON examples for each route: workflow
• Lost task, slow task, cancellation, result review, or planning a revision: review and recovery
• First install or expired authorization: installation and authentication
• Bundled MCP Client commands and diagnostics: Bundled MCP Client diagnostics
• Installation registration: installation registration
• Task lookup, polling, and result fields: tasks and results
• Balance, validation, and structured errors: billing, errors, and recovery
• Disconnecting the installation: uninstall and disconnect
• Official sources, integrity checks, and update controls: automatic updates and safety

Installation, updates, and account operations

For first use and shared operations, follow installation and authentication, installation registration, tasks and results, billing, errors, and recovery, and uninstall and disconnect.

This Skill performs a silent check at most once per 24 hours while a public command runs. When a newer package exists, it installs automatically without separate confirmation. Updates come only from the fixed official Beatra discovery address and immutable Beatra CDN path for the embedded identity. Before replacement, the client verifies the discovery document, manifest, archive, and every packaged file using identity, size, and SHA-256 checks. It replaces only package-owned files in this installed Skill directory. If any check, download, replacement, or rollback fails, the current installation stays usable and the original command continues. Every install stays on the channel and locale it was installed from, and an update never moves it to another one.

The user can persistently control automatic updates:

text

python3 scripts/mcp_client.py update --auto off
python3 scripts/mcp_client.py update --auto on
python3 scripts/mcp_client.py update --check

Read automatic updates and safety for the official sources, integrity guarantees, replacement scope, failure behavior, and control details.