Mark a recall notification as read (default) or unread. Requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
| read | No | if true, mark read; if false, mark unread. Default true | |
| recall_id | Yes | recall id from list_recall_notifications |
| Name | Required | Description | Default |
|---|---|---|---|
| read | Yes | ||
| updated | Yes | ||
| recall_id | 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?
Beyond the annotations, the description reveals the default behavior (read), the optional unread mode, and the API-key requirement. This supplements the structured hints without contradicting them, though it does not describe response or side-effect details (covered by output schema/annotations).
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 short sentences convey the operation and an auth prerequisite with zero filler. The core behavior is front-loaded and the API-key note is kept brief.
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 two-parameter mutation with full schema coverage, idempotency and destructiveness annotations, and an output schema, this description gives the agent everything needed to invoke it correctly. No material gap remains.
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?
Schema description coverage is 100%: recall_id and read are both documented with their meanings and default. The description only restates the default behavior already present in the schema, so it adds no new parameter-level 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 starts with a specific verb and resource: 'Mark a recall notification as read (default) or unread.' This clearly differentiates it from the recall-search and inventory sibling tools, which operate on different resources.
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 context is clear: this tool updates notification read state and requires an API key. It does not explicitly name alternatives or when-not-to-use conditions, but no sibling tool performs the same notification-status mutation, so the implicit usage context is sufficient.
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 clear, distinct resource-action boundaries (inventory vs. watch patterns vs. notifications vs. search). The search tools overlap somewhat—especially search_product_recalls_by_upc, search_product_recalls_from_image, and search_recalls_by_identifier—but their input types and intent are described well enough to avoid major confusion.
The overwhelming majority follow a predictable verb_noun snake_case pattern (add_inventory_product, list_watch_patterns, revoke_api_key). Minor deviations like signup, list_inventory, and search_recalls_by_identifier (instead of search_product_recalls_by_identifier) keep it from being perfectly consistent.
With 19 tools, the server is slightly on the heavier side, but the count is justified by covering several distinct areas: account/key management, inventory, watch patterns, recall search, and notifications. Each tool appears to serve a real purpose, though a few search variants could arguably be consolidated.
The set covers the core lifecycle well: signup, key management, inventory and watch pattern add/list/remove, multiple recall search paths, recall detail lookup, and notification read state. Minor gaps exist, such as no update operation for inventory items or watch patterns and no bulk notification actions, but agents can work around these.