inn_lookup
Проверка российского юрлица по ИНН (ЕГРЮЛ). $0.01 USDC
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | ||
| extra | Yes |
Проверка российского юрлица по ИНН (ЕГРЮЛ). $0.01 USDC
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | ||
| extra | 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?
No annotations are present, so the description carries full responsibility. It mentions cost but does not disclose what information is returned, whether it is read-only, or potential errors/side effects beyond the fee.
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 extremely concise, providing essential information (function, source, cost) without filler. It is well-structured for quick comprehension.
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?
Despite its clarity on purpose, the description lacks critical details about parameter structure, expected output, error handling, and interaction with sibling tools. The generic schema adds no information, leaving the tool under-specified for practical 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 defines only 'args' and 'extra' as generic objects with additionalProperties, and the description provides no details about required parameters (e.g., INN format). The schema itself has no descriptions or constraints.
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 clearly states the tool checks Russian legal entities by INN using EGRUL, and mentions the cost. This is specific and distinguishes it from likely search-oriented sibling tools.
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 usage is implied ('check by INN') but not explicit about when to prefer this over alternatives like ru_search or ru_page. No mention of prerequisites or exclusions.
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 server splits cleanly into INN, Pochta, and RU research domains, and most tools have a distinct purpose. The main confusion risk is pochta_delivery_time vs pochta_tariff, since tariff also includes delivery time, and pochta_offices vs pochta_zip when both are used for index lookup.
Names are consistently lowercase snake_case with clear domain prefixes: inn_, pochta_, ru_. However, the naming is not perfectly uniform because some names are verbs like lookup/track/search, while others are nouns like offices/tariff/zip.
11 tools is a reasonable scope for three covered areas: Russian company lookup, postal services, and Cyrillic search/research. The count is not excessive, but there is enough similarity between a few tools that the set could be slightly trimmed without losing capability.
The Pochta domain is well covered: address normalization, tariffs, delivery times, offices, and tracking are all present. For a read-only RU data API, no critical dead ends are obvious, though the broad 'RU data' scope could plausibly include more data sources beyond INN, postal, and web search.