lookup_dns_monitorCheck DNS records for a domain and compare against the previous snapshot. Detects record changes over time. Use when monitoring DNS configuration.
| Name | Required | Description | Default |
|---|---|---|---|
| types | No | DNS record types to check | |
| domain | Yes | Domain to monitor |
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 declare readOnlyHint=true, so the safety profile is already known. The description adds meaningful behavioral context by revealing that the tool maintains a snapshot and compares against it, which is a stateful behavior not apparent from annotations. It does not cover edge cases like first-run behavior, but it goes beyond the annotations.
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 exactly two sentences, front-loaded with the primary action and key differentiator, and contains zero filler. 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?
For a simple read-only tool with annotated safety and 100% schema coverage, the description covers purpose, usage, and a key behavioral trait (snapshot comparison). However, with no output schema, it does not explicitly describe the return value; it only implies the output includes the detected changes. This is a minor gap, but the tool context is still sufficiently complete for selection and invocation.
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 description coverage is 100% (both 'domain' and 'types' have clear descriptions). The tool description does not add any parameter-specific guidance beyond the schema, which already fully explains the parameters. The baseline of 3 applies because the schema does the heavy lifting.
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 states a specific action ('Check DNS records for a domain'), adds the distinctive feature 'compare against the previous snapshot' and 'Detects record changes over time', and clearly separates this tool from sibling lookup_dns by focusing on monitoring and change detection. It is a specific verb+resource with clear scope.
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 explicit usage context with 'Use when monitoring DNS configuration.' It does not, however, mention when not to use the tool or explicitly name an alternative (e.g., lookup_dns), so it lacks the full when/when-not/alternatives structure that would merit a 5.
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.