Regex Tester
regex-testerReal-time regex testing and debugging.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| flags | No | Regex flags (g, i, m, s, u, y) | g |
| pattern | Yes | Regular expression pattern | |
| testString | Yes | String to test against the pattern |
regex-testerReal-time regex testing and debugging.
| Name | Required | Description | Default |
|---|---|---|---|
| flags | No | Regex flags (g, i, m, s, u, y) | g |
| pattern | Yes | Regular expression pattern | |
| testString | Yes | String to test against the pattern |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must carry the full burden. It mentions 'real-time' behavior but does not disclose whether the operation is read-only, what the output format is, or any side effects. This minimal transparency is inadequate for a tool with no other safety signals.
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, front-loaded sentence with zero filler. While very brief, it is structured efficiently, though it sacrifices informative content for brevity.
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?
With no output schema and no annotations, the description should explain what 'testing and debugging' returns or how the results are presented. It does not, leaving the agent uncertain about the tool's behavior beyond the input parameters.
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?
All three parameters (pattern, testString, flags) have descriptive entries in the schema, achieving 100% coverage, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides.
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 identifies a regex testing/debugging tool with a specific verb+resource. With no sibling tools focused on regex, it inherently distinguishes itself. However, it lacks the explicit differentiation or added context seen in top-tier descriptions.
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 is provided on when to use this tool, its prerequisites, or alternatives. The description merely states what the tool does, leaving the agent to infer its place in a workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.
Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.
202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.
The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.