Convert a datetime between IANA timezones.
| Name | Required | Description | Default |
|---|---|---|---|
| datetime | Yes | Datetime in ISO format (YYYY-MM-DDTHH:mm:ss) | |
| to_timezone | Yes | Target IANA timezone (e.g. Europe/Lisbon) | |
| from_timezone | Yes | Source IANA timezone (e.g. America/New_York) |
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?
With no annotations provided, the description must disclose behavioral traits. It only states the core operation and omits any details about output format, handling of invalid timezones, DST adjustments, or error behavior. This leaves significant gaps for an agent to predict outcomes.
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 delivers its message without fluff. It is appropriately sized for a straightforward utility, though it could slightly benefit from including return-format details, but that is not a conciseness penalty.
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?
There is no output schema, so the description should explain what the tool returns. It does not state the output format or describe behavior for invalid inputs. For a conversion tool, this is a notable gap, making the description incomplete.
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 are fully documented in the input schema with clear descriptions and examples (e.g., 'Europe/Lisbon', ISO format). The tool description adds no extra parameter-specific information, so the schema carries the burden, which it does adequately.
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 a specific verb 'Convert' and clearly identifies the resource: 'a datetime between IANA timezones'. This distinguishes it from sibling tools like convert_currency or decode_base64, leaving no ambiguity about its function.
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 explicit guidance is given on when to use this tool instead of alternatives, nor any exclusions or prerequisites. The described functionality implies usage for timezone conversion, but lacks clear contextual direction.
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.
Each tool has a distinct purpose and target resource or operation. While some tools are thematically related (e.g., detect_secrets and classify_gdpr both analyze text), their specific outputs and use cases are clearly separated by names and descriptions.
Most tools follow a clear verb_noun pattern (convert_currency, generate_uuid, validate_iban), and the noun_to_noun conversion tools (csv_to_json, html_to_text) form a consistent sub-pattern. The mix of verb_noun and X_to_Y is understandable and predictable, though not uniform.
23 tools is on the higher end for a utility server, feeling like a grab-bag of many unrelated functions. While each tool is simple and serves a purpose, the count exceeds the typical well-scoped range, making it heavier than ideal.
The tool coverage is broad but scattered with no clear domain focus. Obvious complementary utilities are missing, such as URL encoding/decoding, YAML conversion, or PDF generation. However, within each small category, core operations are present, so agents can work around gaps.