Software landscape history
The software landscape over time, derived from the temporal software table in one windowed pass: per UTC day, the host-weighted identified/total targets and the k-anonymised vendor shares. Keyless-cacheable.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | Inclusive upper bound (YYYY-MM-DD UTC). Defaults to today. | |
| from | No | Inclusive lower bound (YYYY-MM-DD UTC). Defaults to 90 days ago. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description adds useful behavioral detail: it is computed in 'one windowed pass', grouped by UTC day, host-weighted, k-anonymised, and keyless-cacheable. These details help an agent understand performance, privacy, and response shape semantics.
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 compact, front-loaded with the resource, and every sentence adds value. The heading 'Software landscape history' plus the explanatory sentence and cacheability note are sufficient without filler.
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 read-only, two-optional-parameter time-series tool without an output schema, the description conveys the time granularity, the metrics, and the date defaults. It doesn't describe row counts, edge cases, or the exact JSON return shape, but an agent has enough context to invoke and interpret results.
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?
The input schema already fully documents both optional date parameters with defaults and formats. The description adds nothing new about parameter meaning, so the baseline score of 3 applies.
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 the resource — 'software landscape history' — and the exact output semantics (per UTC day, host-weighted identified/total targets, k-anonymised vendor shares). It is clear enough to distinguish from the non-temporal get_software_stats sibling, though it never explicitly names that alternative.
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 use case is implied by 'over time' and the tool name, but there is no explicit guidance about when to choose this over get_software_stats or other history tools. An agent can infer it is for historical trends, yet the description doesn't state boundary conditions such as 'current snapshot -> get_software_stats'.
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.
Most tools are cleanly separated by resource type: participants, access points, hosts, providers, incidents, anomalies, and SLA each have their own get/list vocabulary. The main ambiguous pairs are get_provider_sla vs get_provider_sla_by_key, list_providers vs list_public_providers, and get_summary vs get_network_summary.
The overall get_/list_ verb_noun pattern is consistent and readable, and plural/singular resource names are mostly clear. There are a few exceptions: get_provider_sla and get_country_providers return collections despite using get_, and list_provider_certs is more of an aggregate posture endpoint than a simple list.
43 tools is well beyond the typical well-scoped MCP surface and will make the tool set harder for an agent to navigate defensibly. The tools are systematically grouped, but this looks like a broad REST API surface rather than a compact, purpose-fit MCP server.
For a read-only monitoring and directory domain, the coverage is unusually complete: list/detail endpoints, histories, SLA tables, churn breakdowns, anomalies, incidents, adoption aggregates, software landscape, and quality checks are all represented. The drill-down routes such as churn totals to churn participants also avoid dead ends.
