case-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@case-mcpconvert 'someXMLParser' to snake_case"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
case-mcp
MCP server: convert a string between case styles. Smart splitting handles
mixed-case identifiers like someXMLParser and my-Mixed_thing.
Tool
convert
{ "text": "someXMLParser", "style": "snake" }→ { "result": "some_xml_parser" }
Supported styles: camel, pascal, snake, constant, kebab, train,
dot, path, title, lower, upper, sentence.
Style | Example output |
camel |
|
pascal |
|
snake |
|
constant |
|
kebab |
|
train |
|
dot |
|
path |
|
title |
|
sentence |
|
Related MCP server: ast-editor
Configure
{ "mcpServers": { "case": { "command": "npx", "args": ["-y", "@mukundakatta/case-mcp"] } } }License
MIT.
Available Tools
1 toolconvertA
Convert a string between case styles: camel, pascal, snake, constant, kebab, train, dot, path, title, lower, upper, sentence. Smart input splitting handles mixed-case input.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| style | Yes | Target style. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions 'smart input splitting handles mixed-case input', which adds some behavioral context. However, it does not disclose output format, edge cases (empty string, non-alphabetic chars), or idempotency.
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 with no redundancy. Every word adds value: the action, the styles list, and the smart splitting behavior. Ideal conciseness.
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?
For a simple tool with no output schema, the description covers the main operation but omits what the tool returns (assumed converted string). It also lacks info on side effects or error behavior. Adequate but incomplete for full autonomous 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?
Schema coverage is 50% (only 'style' has a description). The description adds 'smart input splitting' which hints at how 'text' is processed, but for 'style' it only lists the enum values already in schema. This adds some value but does not compensate fully for the undocumented 'text' parameter.
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 'Convert a string' and the resource 'case styles', listing all 12 supported styles. This makes the purpose unmistakable, and with no sibling tools, differentiation is not needed.
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 string case conversion but provides no explicit guidance on when to use this tool vs alternatives (none exist here). No conditions or prerequisites are given, making it minimal but adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.0- First observed
convert
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of ambiguity between tools. The tool's purpose is clearly distinct by default.
With a single tool, naming consistency is not a concern. The tool name 'convert' is clear and follows a straightforward verb pattern.
The server has exactly one tool for a very narrow domain (case conversion). One tool is appropriate because it covers all necessary case styles through parameters, avoiding excessive complexity.
The tool covers all major case styles (camel, pascal, snake, etc.) and includes smart input splitting. It provides comprehensive case conversion for the intended domain.
Maintenance
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Exact character/word counting, reversal, palindrome checks, indexing, sorting; Unicode-safe.
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