Skip to content
verify mcp Beta VerifyMCP is currently in beta. If you notice any issues, get in touch and we’ll put it right.

ai.pictomancer/image-processing

REMOTE · API.PICTOMANCER.AI · SCANNED SEP 25

Image processing for AI agents: resize, convert, compress, crop, and web-ready AI-generated images.

0 this week 76 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →

Endpoint Security60
Transport & Reachability100
Schema Quality & AI Usability55
  • AI-judged instruction clarity (good).Pass
  • Context-footprint check failed: tool/resource definitions use about 4111 tokens (~411/item across 10 items; 10 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
  • No destabilizing schema changes in the last 30 days.Pass
Tool Coverage97
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 90% of tool parameters carry a description.Partial
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 10 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 10 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

How do I install the ai.pictomancer/image-processing MCP server?

ai.pictomancer/image-processing is a hosted endpoint at https://api.pictomancer.ai/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

remote · api.pictomancer.ai

# add to Claude Code
claude mcp add --transport http ai-pictomancer-image-processing 'https://api.pictomancer.ai/mcp'
// .cursor/mcp.json
{
  "mcpServers": {
    "ai-pictomancer-image-processing": {
      "url": "https://api.pictomancer.ai/mcp"
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "ai-pictomancer-image-processing": {
      "type": "http",
      "url": "https://api.pictomancer.ai/mcp"
    }
  }
}
# ~/.codex/config.toml
[mcp_servers.ai-pictomancer-image-processing]
url = "https://api.pictomancer.ai/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-pictomancer-image-processing": {
      "type": "remote",
      "url": "https://api.pictomancer.ai/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add ai-pictomancer-image-processing --url 'https://api.pictomancer.ai/mcp' --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  ai-pictomancer-image-processing:
    url: "https://api.pictomancer.ai/mcp"
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "ai-pictomancer-image-processing": {
      "Transport": "http",
      "Url": "https://api.pictomancer.ai/mcp"
    }
  }
}
# add to Vellum
assistant mcp add ai-pictomancer-image-processing -t streamable-http -u 'https://api.pictomancer.ai/mcp'
// mcp.json
{
  "mcpServers": {
    "ai-pictomancer-image-processing": {
      "type": "http",
      "url": "https://api.pictomancer.ai/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 25 Sept 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 26 Aug 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 25 Aug 26 0
    • Stability: 0.97 → pass security
  • 19 Aug 26 0
    • Tool “analyze_image” rewrote its description, which is the text the model reads security
    • Tool “optimize_generated_image” rewrote its description, which is the text the model reads security
    • Schema quality: 3692 → 4111 ▼ functional
    • New tool “estimate_cost” functional
    • “optimize_generated_image” reworded the description of “strip” cosmetic
  • 18 Aug 26 0
    • Tool “compress_image” rewrote its description, which is the text the model reads security
    • Tool “convert_image” rewrote its description, which is the text the model reads security
    • Tool “crop_image” rewrote its description, which is the text the model reads security
    • Tool “resize_image” rewrote its description, which is the text the model reads security
    • Schema quality: 342 → 410 ▼ functional
    • Server version: Agent-to-agent image processing: resize, convert, compress, and pipeline operations. Sub-50ms latency, USDC micropayments via x402. → Agent-to-agent image processing: resize, convert, compress, crop, pipeline, and one-call optimization of AI-generated images for the web. Sub-50ms latency, USDC micropayments via x402. functional
    • New tool “optimize_generated_image” functional
    • “compress_image” added an optional parameter “denoise” cosmetic
    • “compress_image” added an optional parameter “equalize” cosmetic
    • “compress_image” added an optional parameter “sharpen” cosmetic
    • “convert_image” added an optional parameter “denoise” cosmetic
    • “convert_image” added an optional parameter “equalize” cosmetic
    • “convert_image” added an optional parameter “sharpen” cosmetic
    • “crop_image” added an optional parameter “denoise” cosmetic
    • “crop_image” added an optional parameter “equalize” cosmetic
    • “crop_image” added an optional parameter “sharpen” cosmetic
    • “resize_image” added an optional parameter “denoise” cosmetic
    • “resize_image” added an optional parameter “equalize” cosmetic
    • “resize_image” added an optional parameter “sharpen” cosmetic
  • 11 Aug 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 7 Aug 26 0
    • The server no longer declares the “experimental” capability functional
  • 3 Aug 26 0
    • Tool “compress_image” rewrote its description, which is the text the model reads security
    • Tool “convert_image” rewrote its description, which is the text the model reads security
    • Tool “crop_image” rewrote its description, which is the text the model reads security
    • Tool “resize_image” rewrote its description, which is the text the model reads security
    • Schema quality: 253 → 342 ▼ functional
    • “compress_image” added an optional parameter “autorot” cosmetic
    • “compress_image” added an optional parameter “quality_target” cosmetic
    • “convert_image” added an optional parameter “autorot” cosmetic
    • “convert_image” added an optional parameter “quality_target” cosmetic
    • “crop_image” added an optional parameter “autorot” cosmetic
    • “crop_image” added an optional parameter “gravity” cosmetic
    • “crop_image” added an optional parameter “threshold” cosmetic
    • “crop_image” added an optional parameter “trim” cosmetic
    • “resize_image” added an optional parameter “autorot” cosmetic
    • “resize_image” added an optional parameter “gravity” cosmetic
    • “resize_image” added an optional parameter “height” cosmetic
    • “resize_image” added an optional parameter “width” cosmetic
    • “crop_image” reworded the description of “height” cosmetic
    • “crop_image” reworded the description of “width” cosmetic
    • “crop_image” reworded the description of “x” cosmetic
    • “crop_image” reworded the description of “y” cosmetic
    • “crop_image” made “height” optional cosmetic
    • “crop_image” made “width” optional cosmetic
    • “crop_image” made “x” optional cosmetic
    • “crop_image” made “y” optional cosmetic
Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 25 Sept 2026 · Probed https://api.pictomancer.ai/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_256_GCM_SHA384 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=api.pictomancer.ai CN=YE1,O=Let's Encrypt,C=US 21 Sept 2026 20 Dec 2026 ECDSA 256 ECDSA-SHA384 59848775185b49f1630b0b20cf2665b37b8
SANs: api.pictomancer.ai
CN=YE1,O=Let's Encrypt,C=US (CA) CN=Root YE,O=ISRG,C=US 3 Sept 2025 2 Sept 2028 ECDSA 384 ECDSA-SHA384 5ddd70dd31f801c85c186a7a04b80afe
CN=Root YE,O=ISRG,C=US (CA) CN=ISRG Root X2,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 ECDSA-SHA384 872165fc34b6e5fba8add5b3705fb53a
CN=ISRG Root X2,O=Internet Security Research Group,C=US (CA) CN=ISRG Root X1,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 SHA256-RSA 6c8f1dc727c7117f7baf853ac980f9cd

Background: What to check on a remote MCP endpoint →

DNSSEC secure

Validation of api.pictomancer.ai. — Secure

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
ai. present 3799 8 Verified
pictomancer.ai. present 2371 13 Verified
api.pictomancer.ai. Verified address RRset verified with the apex keys
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200

Background: How OAuth 2.1 works in the 2026 MCP spec →

Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://api.pictomancer.ai/mcp Verified 200
http (plaintext) http://api.pictomancer.ai/mcp HTTPS enforced 301 https://api.pictomancer.ai/mcp
MCP tools · 10 exposed · ~4,111 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
analyze_image ~173

Analyze an image Fetch an image from a URL or base64 and return its metadata: size in bytes, pixel dimensions, source format, and what it costs every supported vision model in tokens. Always free. Dimensions are omitted if the image header cannot be read. Also reports whether the input carries a C2PA (Content Credentials) manifest and in which container; the manifest is not validated. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **Example Response:** ```json { "size_bytes": 1, "c2pa_manifest": true } ```

NameTypeReqDescription
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).

No output schema declared.

No examples provided.

compress_image ~565

Compress an image Re-encode an image with quality/format options to reduce file size. Supports jpeg, png, webp, tiff, gif. Instead of a q number you can set quality_target (0-1]: the smallest file with SSIM at or above the target, searched on the worker (jpeg, webp, avif; flat surcharge; outcome reported in X-Pictomancer-Quality-* headers). If the output is not smaller than the input, the request is free (X-Pig-Billed: 0) and does not consume free-tier quota. Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

NameTypeReqDescription
autorotboolean–Apply EXIF orientation before compressing. Opt-in; default false, which preserves current byte-for-byte behavior.
deliverystring––
denoiseinteger–Median denoise before compressing: radius 1-3 (window 3x3 to 7x7). Opt-in; no surcharge.
equalizeboolean–Auto-contrast (histogram equalisation of the value channel; hue and saturation preserved) before compressing. Opt-in.
formatstring–Output format: jpeg, png, webp, tiff, gif, or avif. If omitted, the original format is preserved.
qinteger–Quality (1-100). Lower = smaller file. Typical values: 60-80 for web, 85-95 for print. Maps to libvips Q parameter.
quality_targetnumber–Target SSIM (0-1]: the worker searches for the smallest file that still scores at least this. Alternative to q; mutually exclusive with it. Requires an explicit format among jpeg, webp, avif. Carries…
sharpenboolean–Unsharp-mask sharpen after compressing (libvips defaults). Opt-in.
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).
stripboolean–Strip metadata (EXIF, ICC profile, etc.) from the output. Reduces file size slightly.

No output schema declared.

No examples provided.

convert_image ~565

Convert image format Convert an image to a different format (jpeg, png, webp, tiff, gif, avif). Optionally set quality, strip metadata, enable lossless mode (webp, avif), or tune encoder effort (avif). Instead of a q number you can set quality_target (0-1]: the smallest file with SSIM at or above the target, searched on the worker (jpeg, webp, avif; flat surcharge; outcome reported in X-Pictomancer-Quality-* headers). Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

NameTypeReqDescription
autorotboolean–Apply EXIF orientation before converting. Opt-in; default false, which preserves current byte-for-byte behavior.
deliverystring––
denoiseinteger–Median denoise before converting: radius 1-3 (window 3x3 to 7x7). Opt-in; no surcharge.
effortinteger–AV1 encoder CPU effort (0-9). Higher = smaller file, slower. Only applies to avif.
equalizeboolean–Auto-contrast (histogram equalisation of the value channel; hue and saturation preserved) before converting. Opt-in.
formatstringyesTarget format: jpeg, png, webp, tiff, gif, or avif.
losslessboolean–Enable lossless encoding. Only applies to webp and avif.
qinteger–Quality (1-100). Maps to libvips Q parameter.
quality_targetnumber–Target SSIM (0-1]: the worker searches for the smallest file that still scores at least this. Alternative to q; mutually exclusive with it and with lossless. Only for jpeg, webp, avif. Carries a flat…
sharpenboolean–Unsharp-mask sharpen after converting (libvips defaults). Opt-in.
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).
stripboolean–Strip metadata (EXIF, ICC profile, etc.) from the output.

No output schema declared.

No examples provided.

crop_image ~617

Crop an image Extract a rectangular region from an image, in one of three mutually exclusive modes. Manual: give the top-left corner (x, y) and dimensions (width, height) in pixels. Smart crop: give 'gravity' (attention, entropy, centre) plus width and height; the window is picked automatically, clamped to the source if the target is larger. Trim: set 'trim: true' (optional 'threshold') to remove a uniform background border via content detection; the applied rect is reported in X-Pictomancer-Trim-* headers. Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

NameTypeReqDescription
autorotboolean–Apply EXIF orientation before cropping. Opt-in; default false, which preserves current byte-for-byte behavior.
deliverystring––
denoiseinteger–Median denoise before cropping: radius 1-3 (window 3x3 to 7x7). Opt-in; no surcharge.
equalizeboolean–Auto-contrast (histogram equalisation of the value channel; hue and saturation preserved) before cropping. Opt-in.
formatstring–Output format: jpeg, png, webp, tiff, gif, or avif. If omitted, the original format is preserved.
gravitystring–Smart-crop mode: picks the window automatically. One of ('attention', 'entropy', 'centre'). Requires width and height; mutually exclusive with x/y and trim. A target larger than the source clamps to…
heightinteger–Height of the crop rectangle in pixels. Required in manual and gravity modes.
sharpenboolean–Unsharp-mask sharpen after cropping (libvips defaults). Opt-in.
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).
thresholdnumber–Trim sensitivity (must be positive; default 10.0). Only valid together with trim: true.
trimboolean–Trim mode: removes a uniform background border via content detection. Mutually exclusive with x/y/width/height/gravity.
widthinteger–Width of the crop rectangle in pixels. Required in manual and gravity modes.
xinteger–Left edge of the crop rectangle in pixels. Manual mode only.
yinteger–Top edge of the crop rectangle in pixels. Manual mode only.

No output schema declared.

No examples provided.

estimate_cost ~346

Estimate the price of an operation Returns the exact USD price this API would charge for an operation on an input of the given size, without fetching or processing anything. Free. Use it before paying: send X-Max-Cost-USD on the real request to have the API refuse (412) instead of charging more than you allowed. The list price is returned even when the request could end up free (free tier, or a compress that does not shrink the file). ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **Example Response:** ```json { "operation": "Operation", "price_usd": 1.0, "base_usd": 1.0, "surcharges_usd": {}, "size_multiplier": 1.0, "within_free_tier": true, "free_tier_remaining": 1, "currency": "Currency", "network": "Network" } ```

NameTypeReqDescription
formatstring–Requested output format; only avif changes the price.
input_bytesintegeryesSize of the input image in bytes. Get it from analyze_image (free) if you do not know it.
operationstringyesOperation to price. One of resize, compress, convert, crop, optimize_for_vision, optimize_generated, pipeline. analyze is always free.
operationsarray–For pipeline only: the ordered operations, each {type, format?}. Volume discount applies at 3+ operations.
quality_targetboolean–Whether the request will use quality_target (SSIM search surcharge).

No output schema declared.

No examples provided.

get_format_info ~43

Get supported formats and options Returns supported output formats and their configurable options. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

image_pipeline ~209

Run a multi-step image pipeline Chain multiple operations (resize, compress, convert, crop) in sequence. The image is fetched once, then each operation is applied to the output of the previous one. Max 10 operations per pipeline. ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

NameTypeReqDescription
deliverystring––
operationsarrayyesOrdered list of operations to apply sequentially. Each operation receives the output of the previous one. Max 10.
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).

No output schema declared.

No examples provided.

optimize_for_vision ~458

Resize an image for a vision model Resize an image to the largest size a given vision model still benefits from, and report what it costs that model in tokens before and after. Every provider downscales oversized input before counting tokens, so this alone saves bytes and upload latency rather than tokens. Pass max_tokens to trade resolution for tokens: that lever is continuous on Claude, unavailable on OpenAI (cost follows the aspect ratio alone), and on Gemini reaches only a flat 258. An image already within budget is returned untouched and free (X-Pig-Billed: 0). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

NameTypeReqDescription
deliverystring––
formatstring–Output format: jpeg, png, webp, tiff, gif, or avif. If omitted, the original format is preserved.
max_tokensinteger–Optional cap on what the image may cost the target model. Without it the image is resized to the model's own ceiling, which saves bytes and upload latency but no tokens, because every provider alread…
qinteger–Quality (1-100). Maps to libvips Q parameter.
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).
target_modelstringyesVision model the image is being prepared for, e.g. claude-opus-5, gpt-4o, gemini-2.5-pro. Unknown ids are rejected rather than guessed: the wrong limits would silently resize to the wrong size.

No output schema declared.

No examples provided.

optimize_generated_image ~523

Optimize an AI-generated image for the web The step after image generation. gpt-image, DALL-E, Flux, Midjourney and Stable Diffusion hand back 2-8 MB PNGs; this returns the same picture as a web-ready webp (default), avif, jpeg or png, metadata stripped, transparency kept on webp/avif/png. Optional max_dimension caps the longest side (never upscales); optional q or quality_target (smallest file with SSIM >= target, flat surcharge) control quality. Same price as convert. If the result is not smaller than the input it is still returned but free (X-Pig-Billed: 0). X-Pictomancer-Bytes-Before/-After/-Saved-Percent report the saving. The input's C2PA manifest, if any, is reported in X-Pictomancer-C2PA-Input but is not carried over: re-encoding invalidates it. ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

NameTypeReqDescription
deliverystring––
formatstring–Output format: webp (default), avif, jpeg or png. webp, avif and png keep transparency; jpeg flattens it.
max_dimensioninteger–Cap on the longest side in pixels. Larger images are scaled down to fit, aspect ratio preserved; smaller images are never upscaled.
qinteger–Quality (1-100). Maps to libvips Q parameter. Omit to use the encoder default; or set quality_target instead.
quality_targetnumber–Target SSIM (0-1]: the worker searches for the smallest file that still scores at least this. Alternative to q; mutually exclusive with it. Carries a flat surcharge for the extra encodes.
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).
stripboolean–Strip metadata. Defaults to true: generated images carry no EXIF worth keeping. Metadata includes any C2PA manifest, which would be invalid after re-encoding anyway.

No output schema declared.

No examples provided.

resize_image ~612

Resize an image Scale an image by a factor, or fill an exact box. Use 'scale' for uniform scaling, or 'scale_x'/'scale_y' for independent axes (float factors, e.g. 0.5 = half size). Alternatively set 'width'+'height' for fill mode: resize and smart-crop to those exact dimensions in one call (optional 'gravity', default attention). The two modes are mutually exclusive. Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

NameTypeReqDescription
autorotboolean–Apply EXIF orientation before resizing. Opt-in; default false, which preserves current byte-for-byte behavior.
deliverystring––
denoiseinteger–Median denoise before resizing: radius 1-3 (window 3x3 to 7x7). Opt-in; no surcharge.
equalizeboolean–Auto-contrast (histogram equalisation of the value channel; hue and saturation preserved) before resizing. Opt-in.
formatstring–Output format: jpeg, png, webp, tiff, gif, or avif. If omitted, the original format is preserved.
gravitystring–Fill-mode smart-crop strategy: one of ('attention', 'entropy', 'centre'). Only valid together with width and height; defaults to attention.
heightinteger–Target height in pixels for fill mode. Requires width.
scalenumber–Uniform scale factor applied to both axes (e.g. 0.5 = half size). Use this for simple scaling; use scale_x/scale_y for independent axes.
scale_xnumber–Horizontal scale factor (e.g. 0.5 = half width). If only scale_x is given, scale_y defaults to the same value.
scale_ynumber–Vertical scale factor (e.g. 0.75 = 75% height). Optional; defaults to scale_x if omitted.
sharpenboolean–Unsharp-mask sharpen after resizing (libvips defaults). Opt-in.
sourcestringyesImage source: a public URL (https://...) or a base64-encoded string (optionally as a data URI like data:image/png;base64,...).
widthinteger–Target width in pixels for fill mode: resize and smart-crop to these exact dimensions in one call. Requires height. Mutually exclusive with scale/scale_x/scale_y. Upscaling is allowed.

No output schema declared.

No examples provided.

Common questions

What is the ai.pictomancer/image-processing MCP server?

ai.pictomancer/image-processing is an MCP server listed in the public MCP registry as ai.pictomancer/image-processing. Image processing for AI agents: resize, convert, compress, crop, and web-ready AI-generated images. This page covers its hosted endpoint (https://api.pictomancer.ai/mcp).

Is the ai.pictomancer/image-processing MCP server safe to use?

ai.pictomancer/image-processing scores 76 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the ai.pictomancer/image-processing MCP server expose?

ai.pictomancer/image-processing exposes 10 tools: get_format_info, estimate_cost, analyze_image, resize_image, compress_image, and 5 more. Their descriptions and schemas cost roughly 4,111 tokens of context every time the server is loaded.

Does the ai.pictomancer/image-processing MCP server require authentication?

No. We connected to ai.pictomancer/image-processing without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

Is the ai.pictomancer/image-processing MCP server still maintained?

ai.pictomancer/image-processing is still listed as active in the MCP registry. We last reached this channel on 25 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.