Check whether a CVE is in the CISA Known Exploited Vulnerabilities catalog. Returns date added, due date, ransomware association, and required action.
| Name | Required | Description | Default |
|---|---|---|---|
| cve_id | Yes | CVE identifier. |
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 already cover read-only, idempotent, and non-destructive behavior. The description adds value by disclosing the returned fields (date added, due date, ransomware association, required action), which goes beyond what annotations provide. It does not discuss edge cases like CVEs not found in the catalog, but this is acceptable given the simpler tool scope.
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 well-structured sentence that starts with the tool's purpose and immediately lists the useful output fields. There is no filler, redundancy, or unnecessary repetition of the tool name.
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 one-parameter lookup tool, the description covers the action, the target catalog, and the return value fields. It does not specify the response when a CVE is not in the catalog, but the absence of an output schema is partially compensated by listing return fields. Overall it is sufficiently complete for typical use.
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 describes cve_id as a 'CVE identifier' with 100% coverage. The description does not add format guidance (e.g., CVE-YYYY-NNNNN), but the schema description is sufficient for the single parameter. Baseline 3 is appropriate.
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 verb ('Check whether') and a specific resource ('CISA Known Exploited Vulnerabilities catalog'), and enumerates the exact output fields. This clearly distinguishes it from generic CVE tools like cve_lookup or cve_search_by_keyword even without naming them.
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 a clear usage context: determining whether a CVE is in the CISA KEV catalog. It does not explicitly name alternatives or state when not to use the tool, but the narrowly scoped catalog reference makes the intended use obvious.
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.
Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.
Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.
294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.
The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.