get_api_external_get_db_infoIt returns the username and password for accessing the MySQL database containing product information. You can use this endpoint by subscribing to the $350 plan. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 provided, so the description carries the transparency burden. It clearly discloses that the tool returns sensitive MySQL credentials, but it does not mention failure modes, authorization behavior, or security considerations for handling the returned password.
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 three short sentences and every sentence earns its place: what is returned, which database it accesses, subscription requirement, and billing cost. It is front-loaded and contains no fluff.
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 zero-parameter, no-output-schema, low-complexity tool, the description is reasonably complete: it explains the returned values, the data domain, and the access/billing context. It is slightly limited by the lack of usage-vs-alternative context and no error or negative-case information.
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 tool has no parameters and the schema coverage is 100%, so there is no hidden input semantic gap. The baseline of 4 applies because the schema fully describes the input surface and the description correctly adds no redundant parameter detail.
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 exactly what the tool does: 'returns the username and password for accessing the MySQL database containing product information.' It uses a specific verb, identifies the exact resource, and is clearly distinct from the sibling product-data 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 description gives no guidance about when this tool should be used versus alternatives. It only mentions the $350 plan subscription and per-call billing, which is a prerequisite rather than an actionable usage guideline.
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 have clearly distinct purposes: search, paginated product listing, product-by-market pricing, price history, recent products, and market names. The main overlap is that product_of_market can optionally include price history while a dedicated history tool also exists, so an agent might occasionally choose between them.
All tool names share the get_api_external_ prefix, but the remaining portion is inconsistent: some use camelCase (getProducts, marketList), some use snake_case (get_db_info, product_of_market), and some use bare nouns (history, last, search). This mixed convention makes the tool surface feel less predictable.
Seven tools is well-scoped for a product barcode and pricing API. Each tool covers a meaningful query type without unnecessary bloat or redundancy.
The read-oriented surface covers searching, listing, product-market pricing, price history, recent updates, and market filter data. A minor gap is the lack of a dedicated product-details-by-barcode endpoint across all stores without requiring a store name, though search partially fills this.