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Image Processing MCP Server

by pictomancer Your server? Claim it
answering

Image Processing is answering right now. Last checked 9 min ago. It exposes 10 tools.

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

Uptime history 47 days of history · worst day 90%
47 days agonow
100.0%
Uptime 24h
91 of 91 checks
10
Tools
read from the server
181 ms
Response time
average over 24h
open, no key
Access
streamable-http

What changed 14

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 17 August 2026. No other catalogue keeps this.

19 Aug 2 tool descriptions were rewritten analyze_image, optimize_generated_image
19 Aug a tool changed the parameters it asks for optimize_generated_image
18 Aug 2 tools appeared estimate_cost, optimize_generated_image
18 Aug a tool changed version
17 Aug 4 tool descriptions were rewritten compress_image, convert_image, crop_image and 1 more
17 Aug 4 tools changed the parameters they ask for compress_image, convert_image, crop_image and 1 more

Nothing serious here today

Today is the operative word: we check Image Processing every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 9 min ago.

run in your terminal
claude mcp add image-processing --transport http https://api.pictomancer.ai/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "image-processing": {
      "url": "https://api.pictomancer.ai/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.image-processing]
url = "https://api.pictomancer.ai/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "image-processing": {
      "url": "https://api.pictomancer.ai/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "image-processing": {
      "url": "https://api.pictomancer.ai/mcp"
    }
  }
}

Available tools 10

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

optimize
optimize_for_vision
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" ```
optimize_generated_image
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" ```
analyze
analyze_image
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 } ```
compress
compress_image
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" ```
convert
convert_image
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" ```
crop
crop_image
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" ```
estimate
estimate_cost
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" } ```
format
get_format_info
Get supported formats and options Returns supported output formats and their configurable options. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json
image
image_pipeline
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" ```
resize
resize_image
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" ```

Endpoints

URLTransportStateLatencyChecked
https://api.pictomancer.ai/mcp streamable-http answering 245 ms 9 min ago

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Image Processing — questions

Answers built from our own checks of this server.

What can Image Processing do?
It exposes 10 tools, read directly from the server on our last check. Among them: analyze_image, compress_image, convert_image, crop_image, estimate_cost, get_format_info and 4 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is Image Processing working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 181 ms. The bar chart above shows every period we have measured.
How do I connect Image Processing?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Image Processing need an API key?
No. Image Processing completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 10 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Image Processing?
It answers our handshake in 181 ms on average, which is faster than 70% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.