security_totp_generateGenerate a TOTP secret and provisioning URI for 2FA setup.
| Name | Required | Description | Default |
|---|---|---|---|
| digits | No | Number of digits in the code | |
| period | No | Time step in seconds | |
| secret | Yes | Base32-encoded shared secret |
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?
The annotation readOnlyHint=true already covers the safety profile. The description adds that it produces both a secret and a provisioning URI, but it does not clarify that the 'secret' parameter must be provided as input, potentially implying a random secret is generated. This ambiguity is a meaningful gap beyond what annotations convey.
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 with no filler or repetition. Every word earns its place, and it is easily scannable.
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 conveys the core purpose and benefits from well-documented parameters and annotations, but it leaves ambiguity about whether the secret is generated or provided as input, and the exact return format is unspecified. No output schema further increases the need for description detail, so this is a moderate gap.
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 have detailed descriptions in the input schema (digits, period, and base32 secret), so the schema already provides full parameter semantics. The tool description adds no additional information about parameters beyond what the schema 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 uses the specific verb 'Generate' and clearly names the two outputs ('TOTP secret and provisioning URI'), which distinguishes this from sibling tools like dev_password_generate or security_encrypt. Adding 'for 2FA setup' provides clear scope and purpose.
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 phrase 'for 2FA setup' gives clear context on when to use the tool. However, it does not explicitly mention when not to use it or alternatives among sibling tools. This is a clear context without exclusions, hence a 4.
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.
The tools are grouped into clear categories (dev, lookup, security, text, transform), which helps with disambiguation, but within categories there is some overlap. For example, lookup_ssl and lookup_ssl_cert_expiry both handle SSL certificates, and dev_url_encode/dev_url_decode are closely related but distinct. Most tools have unique purposes, but a few could be confused without careful reading of descriptions.
The naming follows a consistent snake_case pattern with a clear prefix structure (dev_, lookup_, security_, text_, transform_), which aids in organization. However, there are minor deviations like dev_cron_describe using 'describe' while others use verbs like 'generate' or 'convert', and some tools have longer names that break the verb_noun pattern slightly. Overall, the naming is predictable and readable.
With 49 tools, the count is excessive for a utility server, making it overwhelming and likely to cause confusion or inefficiency. While the tools cover many use cases, a more focused set of 15-25 tools would be more manageable and better scoped. The high number suggests feature bloat rather than a coherent, minimal surface.
The tool set is highly complete for its utility and development support domain, covering a wide range of operations from data transformation and security to lookups and text processing. There are no obvious gaps; each category provides comprehensive coverage, such as full text encoding/decoding, security functions, and various lookup capabilities, ensuring agents can handle diverse tasks without dead ends.