Return entities added or updated since a given ISO date for a chosen source list. The four official lists do not all expose a public delta feed, so this filters the cached snapshot by listedOn.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum matches to return. Defaults vary per tool. | |
| since | Yes | ISO date string (e.g. 2026-01-01) to compute the delta from. | |
| source | Yes |
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 description discloses a non-obvious behavioral trait: because not all official lists expose a public delta feed, results are derived by filtering the cached snapshot by listedOn. This adds real context beyond the readOnlyHint and idempotentHint annotations and helps the agent understand possible data limitations.
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?
Two sentences with no filler. The operation is front-loaded, and the second sentence earns its place by explaining an important implementation caveat.
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 relatively simple read-only delta query, the description plus schema covers the key details: since, source, and the cached-snapshot behavior. It is slightly incomplete because there is no output schema and the description does not describe response shape or pagination behavior, leaving some inference to the agent.
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 schema already documents since and limit reasonably well, and source is constrained by an enum. The description adds some context by calling the sources the 'four official lists,' but it does not clarify limit behavior or explain the source enum values beyond that. Overall the description provides only modest extra parameter meaning.
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 and resource: returning entities added or updated since an ISO date for a selected source list. This clearly distinguishes it from sibling sanctions tools like sanctions_get_entity or sanctions_screen_entity, which fetch or screen rather than compute deltas.
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 clearly frames the intended use case: get a delta of entities added or updated since a date for one of four official lists. It does not explicitly name alternatives or exclusions, but the cache caveat gives useful context about feasibility and behavior.
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.