Tanod MCP server

imagepeek: compute an image's BlurHash

image_blurhash

Read-onlyIdempotent

Generate a BlurHash placeholder string from an image URL or base64, with adjustable 1–9 components, to display a blurred preview while the full image loads.

Instructions

imagepeek: Generate a BlurHash placeholder string for an image. For the palette use image_colors. Returns the BlurHash string of an image (the published woltapp algorithm, identical to the reference package), with x_components and y_components 1-9 (default 4 x 3), for blurred placeholders while the real image loads. Reads PNG, JPEG, WebP, GIF, TIFF, BMP, ICO and AVIF; other formats and images over 40 megapixels are refused (not charged). Images are never logged or stored. Typically 0.5-2 s. Price: USD 0.002. Free: 3 imagepeek calls per IP per UTC day. Docs: https://tanod.dev/learn/blurhash-api.html

Input Schema

TableJSON Schema

Name	Required	Description
`url`	No	Public http(s) URL of the image (at most 10 MB; private, internal and IP-literal hosts are refused); or use image_base64.
`auto_orient`	No	Apply the EXIF orientation first (default true).
`image_base64`	No	The image as standard or url-safe base64 (at most 10 MB decoded; a data:image/...;base64, prefix is fine); or use url.
`x_components`	No	Horizontal components (1-9, default 4): more detail, a longer hash.
`y_components`	No	Vertical components (1-9, default 3).

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No	Only on an error result: an object {code, message}, or the reason string of an x402 PaymentRequired object.
`input`	No
`notes`	No
`source`	No
`blurhash`	No
`final_url`	No
`operation`	No
`source_url`	No
`x_components`	No
`y_components`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Oct 15, 2026

TDQS

A4.4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds substantial context beyond the read-only/idempotent annotations: supported formats (PNG, JPEG, WebP, GIF, TIFF, BMP, ICO, AVIF), refusal behavior for other formats and images over 40 MP with 'not charged', privacy ('never logged or stored'), latency (0.5-2 s), price, and free-tier quota. This is exactly the behavioral disclosure that helps an agent decide and set expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Dense but front-loaded: purpose, alternative, return value, parameters, then formats/limits/privacy/pricing. Almost every clause carries decision-relevant information, though the pricing/free-tier/docs tail is somewhat administrative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists so exact return structure needn't be described, yet the description still states it returns the BlurHash string using the published woltapp algorithm. Combined with format limits, latency, and pricing, the agent has everything needed to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents url, image_base64, auto_orient, x_components and y_components fully. The description restates the x/y component range and defaults but adds no syntax or semantics beyond what the schema provides, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (generate) and resource (BlurHash placeholder string for an image), and explicitly names the sibling to use for a different need ('For the palette use image_colors'). An agent can distinguish this from image_colors, image_hash, and image_metadata without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context for when this applies ('blurred placeholders while the real image loads') and routes the palette use case to image_colors. It does not spell out explicit when-not conditions beyond the format/size refusals, but the routing guidance is concrete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server