rnv-color-mcp
Server Details
rnv-color-mcp, a hosted color-workflow MCP server (Python, Streamable HTTP).
Tools: mix (including Kubelka-Munk paint physics), convert between formats, generate harmonies, transform text case, and save/list/get named palettes. It resolves hex / CSS / custom brand color names and refuses unknown colors rather than guessing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.3/5 across 9 of 9 tools scored. Lowest: 3.5/5.
The color tools are clearly distinct in purpose, but the inclusion of transform_text, a text transformation tool, creates ambiguity as it is unrelated to the color domain. This outlier may cause agent misselection.
All tools follow a consistent verb_noun naming pattern (e.g., color_difference, list_palettes, save_palette). Even the outlier transform_text adheres to this pattern, so no naming inconsistency exists within the set.
With 9 tools covering color manipulation and palette management, the count is well-scoped for the server's purpose. It provides sufficient functionality without being overwhelming.
The color tools cover conversion, difference, contrast, harmony, mixing, and palette CRUD (get, list, save). Missing explicit delete for palettes, but upsert covers overwrite. The unrelated transform_text tool adds an incomplete feature outside the domain, slightly lowering completeness.
Available Tools
9 toolscolor_differenceAInspect
Perceptual difference (Delta-E) between two colors. color1 and color2 accept a hex, CSS name, RNV brand name, or saved-palette reference. method is 'ciede2000' (default, modern standard) or 'cie76'. A value near 1.0 is the threshold the eye can just notice; larger means more different. Returns the value and a plain-language interpretation.
| Name | Required | Description | Default |
|---|---|---|---|
| color1 | Yes | ||
| color2 | Yes | ||
| method | No | ciede2000 |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool returns a value and plain-language interpretation, and explains the threshold meaning. It is a non-destructive computation, so no destructive behavior needs disclosure. The description is transparent about outputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: 3 sentences covering purpose, inputs, and output interpretation. No extraneous information, every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (3 params, 2 required) and presence of an output schema, the description provides sufficient context: input formats, method options, output meaning. It is complete for the agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It fully explains all 3 parameters: color1/color2 accept multiple formats (hex, CSS name, RNV brand name, saved-palette reference) and method is 'ciede2000' or 'cie76' with default. This adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb+resource: 'Perceptual difference (Delta-E) between two colors.' It distinguishes itself from sibling tools like contrast_check, convert_color, and mix_colors by focusing on perceptual difference calculation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on input formats (hex, CSS name, RNV brand name, saved-palette reference) and method options with defaults. It explains the interpretation of the output value. However, it does not explicitly contrast with sibling tools or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
contrast_checkAInspect
WCAG contrast ratio between a foreground and background color, for accessibility. Both accept a hex, CSS name, RNV brand name, or saved-palette reference. Returns the ratio (1.0-21.0) plus pass/fail for AA and AAA at normal and large text sizes and for UI components. Use this to check if text will be readable on a background.
| Name | Required | Description | Default |
|---|---|---|---|
| background | Yes | ||
| foreground | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the output format (ratio and pass/fail for AA/AAA at normal/large text and UI components). No annotations provided, so description carries full burden; no side effects disclosed as none exist. Good transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first covers purpose and accepted inputs, second covers output and usage. No wasted words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no nested objects), the description fully covers purpose, parameters, and output. Output schema exists but description summarizes it adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description fully explains that both foreground and background accept hex, CSS name, RNV brand name, or saved-palette reference, adding significant meaning beyond the plain string type in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool checks WCAG contrast ratio for accessibility, using a specific verb ('check') and resource ('contrast ratio between foreground and background color'). Distinguishes from siblings like 'color_difference' by specifying the accessibility focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to check if text will be readable on a background', providing clear usage context. Does not mention when not to use or alternatives, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_colorAInspect
Convert a color between formats. Input accepts a hex, CSS name, RNV brand name, or saved-palette reference. With to set to one of hex/rgb/hsv/hsl/lab, returns just that format; otherwise returns all of them.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | ||
| color | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full behavioral burden. Discloses input types and output behavior but does not mention error handling, alpha channel support, or behavior on invalid input. Adequate for a simple conversion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundancy. First sentence states action and accepted inputs, second specifies output conditional logic. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description covers inputs and output behavior for a conversion tool with two parameters and existing output schema. Lacks mention of format standardization (e.g., hex with/without #) but still fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description fully explains both parameters: `color` accepts specific formats, `to` optionally restricts output. Does not specify exact enum strings (e.g., 'hex' vs 'HEX') but adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States 'Convert a color between formats' and specifies accepted input types (hex, CSS name, RNV brand name, saved-palette reference) and output behavior (return specific format if `to` is set, otherwise all). Clearly distinguishes from sibling tools like generate_harmony and mix_colors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for color format conversion with specific input types. Does not explicitly state when not to use or compare to siblings, but the context of sibling names provides differentiation. No exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_harmonyAInspect
Generate a color harmony from a base color. base accepts a hex, CSS name, RNV brand name, or saved-palette reference (e.g. 'Spring line:2'). scheme is one of: complementary, analogous, triadic, split-complementary, tetradic (a.k.a. square), monochromatic, compound. Returns a list of hex colors.
| Name | Required | Description | Default |
|---|---|---|---|
| base | Yes | ||
| scheme | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It discloses return type (list of hex colors) and acceptable inputs, but misses potential error behavior or side effects. Adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One concise paragraph with no redundancy. Every sentence adds necessary information about input formats and return output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two required parameters and an output schema, description covers input formats and expected output. Lacks details on error handling or edge cases, but overall sufficiently complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, description provides essential parameter details: base accepts multiple formats (including saved-palette references) and scheme lists all valid options. This significantly aids correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool generates a color harmony from a base color, specifying accepted input formats (hex, CSS name, etc.) and scheme options. It distinguishes itself from sibling tools like convert_color and get_palette by focusing on harmony generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating color harmonies but does not explicitly state when to use this tool over alternatives. No exclusion criteria or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_paletteAInspect
Retrieve one saved palette by name, returning its colors and metadata. Returns null if no palette by that name exists.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries burden. It discloses null return for missing names, a key behavior. However, lacks explicit statement that tool is read-only, idempotent, or any auth requirements. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, front-loaded sentences with zero waste. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity, single param, and presence of output schema, description is mostly complete. Could mention read-only nature for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
One parameter 'name' with schema coverage 0%. Description adds context that it's a palette name, but no format, case sensitivity, or constraints. Marginal value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Retrieve' and resource 'saved palette by name', clearly distinguishing from siblings like list_palettes. States output (colors and metadata) and null return if not found.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage when a specific palette name is known, but no explicit guidance on when to use this vs. list_palettes or save_palette. No when-not or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_palettesAInspect
List every saved palette as name + colors.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It states 'List every saved palette' but does not mention potential limits, pagination, or default behavior if there are many palettes. This omission could lead to incorrect agent expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded with purpose. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic output (name + colors), which is adequate given the output schema exists. However, it lacks detail on ordering, potential empty results, or performance implications. Could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the description has no need to add parameter semantics. The schema coverage is 100%, so baseline is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List', the resource 'every saved palette', and the output format 'name + colors'. It distinguishes from sibling tools like 'get_palette' (singular) and 'save_palette' (write).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool vs alternatives (e.g., 'get_palette' for a specific palette). The description lacks context for usage decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mix_colorsAInspect
Blend up to 12 colors into one. Each color may be a hex (#d2bc93), a CSS name (red), an RNV brand name (brand gold, near-black), or a saved-palette reference (Spring line, or 'Spring line:2' for its 2nd swatch). Optional integer weights bias the blend (defaults to equal). mode selects the model: rgb/hsv/lab are digital blends (lab is perceptual and the default); paint mixes pigments via Kubelka-Munk physics (colors darken like real paint); ryb is the artist's color wheel; cmy is subtractive like printer inks. Returns hex and rgb.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | lab | |
| colors | Yes | ||
| weights | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It thoroughly explains the blending behavior, including different color models (digital, paint, RYB, CMYK), input types (hex, CSS name, brand name, palette references), and return format (hex and rgb). There is no mention of side effects, which is appropriate for a non-destructive blend.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that packs comprehensive information without unnecessary words. While it is clear and efficient, it could be slightly improved by using bullet points for the mode options, but it is still highly readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers most essential aspects: input types, modes, weights, and return format. Given the tool's complexity, it is reasonably complete. However, it omits potential edge cases like invalid color strings or mismatched weights length, and does not mention the capabilities of the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description fully compensates by explaining each parameter: colors (array of strings with examples), weights (optional integers, defaults to equal), and mode (string with default and enumerated options). This provides clear semantics beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool blends up to 12 colors into one, with specific input types and modes. It distinguishes from sibling tools like convert_color (single color conversion) and generate_harmony (color harmony generation) by focusing on blending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (blending colors), provides default behavior (mode=lab, equal weights), and lists available modes. However, it does not explicitly mention when not to use it or suggest alternative tools for other color operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
save_paletteAInspect
Persist a named color palette for later retrieval with get_palette or list_palettes. Use when the user wants to keep a set of colors under a name for reuse across sessions, such as a brand or launch palette. colors is a list of hex values; reusing an existing name overwrites that palette (upsert). Optional notes are stored as the palette's description. The saved name can then be referenced by other tools (mix_colors, convert_color, generate_harmony) as a palette reference. Author is recorded as RNVizion.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| notes | No | ||
| colors | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fully carries burden: discloses upsert behavior, that optional notes become the palette's description, that author is recorded, and that saved name can be referenced by other tools. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each adding distinct value: main purpose, usage, parameter details, and cross-tool references. No redundancy or unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, three parameters, and an output schema (exists), the description covers all essential aspects: purpose, when to use, parameter semantics, behavior, and relations to sibling tools. Fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but description compensates by explaining colors as a list of hex values, name is the key for upsert, and notes are stored as description. Adds essential meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it persists a named color palette for later retrieval, and explicitly names sibling tools (get_palette, list_palettes) for retrieval, distinguishing this from other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (user wants to keep colors for reuse across sessions), explains upsert behavior (overwrite on reuse), and mentions other tools that can reference the saved palette, providing comprehensive usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
transform_textAInspect
Apply an exact, deterministic text transformation. operation is one of: UPPERCASE, lowercase, 'Title Case', 'Sentence case', camelCase, PascalCase, snake_case, CONSTANT_CASE, kebab-case, dot.case, 'iNVERTED cASE'. Use this rather than converting case by hand.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| operation | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It describes the transformation as 'exact, deterministic,' indicating predictable, pure behavior. No additional behavioral traits (e.g., side effects) are needed for this simple function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words, front-loaded with purpose and supported by a complete list of operations. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description provides sufficient context: purpose, operation options, and a usage hint. Could include a brief note on case sensitivity or idempotency, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameter descriptions in the schema, but the description enumerates valid operation values, compensating for missing enums. The 'text' parameter is self-explanatory, though not elaborated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool applies exact deterministic text transformations and lists all supported case styles. It distinguishes itself from sibling tools (all color-related) by focusing on text case manipulation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using this tool rather than manual case conversion, providing a clear usage context. It does not specify when not to use it, but siblings are unrelated, so exclusions are unnecessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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