Recraft AI MCP connector for AI agents

Recraft AI MCP tools for AI agents

CALL ANY TOOL

12 tools covering creative, create, crisp.

recraftmcp_create_style

Create a custom style from one or more reference images. pro

Create a custom style from one or more reference images. provide images via urls or base64-encoded data. the style parameter defines the base style type.

Parameters

Name

Type

Required

Description

input_image_type

string

Required

Visual image type for the style

input_style_images_b64

array

Optional

Base64-encoded reference images (1–5). Mutually exclusive with input_style_images_urls.

input_style_images_urls

array

Optional

Publicly accessible HTTPS URLs of reference images (1–5). Mutually exclusive with input_style_images_b64.

model

string

Optional

Model version. Default: recraftv4_1.

private

boolean

Optional

Whether the style is private.

style_prompt

string

Optional

Optional text prompt to refine style (1–1000 chars).

recraftmcp_creative_upscale

Upscale an image using creative ai enhancement. returns the

recraftmcp_crisp_upscale

Upscale an image with sharp, crisp quality enhancement. retu

recraftmcp_delete_style

Delete a custom style by its id.

recraftmcp_erase_region

Erase a masked region from an image, filling it with content

recraftmcp_generate_background

Generate a background for a masked region of an image based

recraftmcp_generate_image

Generate an image from a text prompt. returns image urls and

recraftmcp_get_style

Get details of a specific style by its id.

recraftmcp_get_user

Get information about the current user including id, email,

recraftmcp_image_to_image

Transform an existing image based on a text prompt. the stre

recraftmcp_inpaint_image

Fill in a masked region of an image based on a text prompt.

recraftmcp_list_styles

List all custom styles created by the current user.

Build your Agent

Same auth pattern across every framework.

from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="recraftmcp")

mcp = MultiServerMCPClient({
    "recraftmcp": {
        "url": "https://mcp.scalekit.com/recraftmcp",
        "headers": {"Authorization": "Bearer " + token}
    }
})
tools = await mcp.get_tools()

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "recraftmcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/recraftmcp
// Pass: Authorization: Bearer + token

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "recraftmcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/recraftmcp
// Pass: Authorization: Bearer + token

from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="recraftmcp")
# Connect to MCP at https://mcp.scalekit.com/recraftmcp
# Pass: Authorization: Bearer + token

Try these prompts

Paste any prompt into your agent to get started.

Get started

Copy the prompt

Copied

Convert a raster image to a vector format?

Copy the prompt

Copied

Suggest the best Recraft image generation model for a given user request?

Advanced

Copy the prompt

Copied

List available Recraft subscription plans with their credits, refill periods, and pricing?

Copy the prompt

Copied

Issue an upload URL for a direct image upload?

SEE HOW AUTH WORKS

User authorises once. Every agent call after uses their token with scope enforcement.

Authorize

Your user connects

Recraft AI MCP

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Recraft AI MCP

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Recraft AI MCP

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Recraft AI MCP

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other connectors.

No items found.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

Other connector libraries treat auth as a demo afterthought.

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.

// shared token
 audit → bot_service_account

 // scalekit
 audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

One connector today. Ten tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Recraft AI as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Recraft AI OAuth token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Recraft AI?
Yes. Pass a tool name filter to listScopedTools so the design agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Recraft AI.

What happens when a user revokes Recraft AI access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Whose Recraft credits do image generations consume?
The authorizing user's. Generations, upscales, and style edits bill to that user's Recraft account, so design spend stays attributable per teammate.

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit