Fetch the full email thread for an inbox item
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | Inbox item id |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | No |
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 declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the 'full thread' scope but does not describe other behavioral details; however, with annotations present, the bar is lower.
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?
A single, front-loaded sentence with no filler. It states exactly what the tool does and leaves out irrelevant detail.
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?
The tool is simple with one required parameter, safe-read annotations, and an output schema available. The description is sufficient for a correct call given these supporting signals.
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 describes item_id as 'Inbox item id' with 100% coverage, so the only parameter is already documented. The description does not add extra meaning beyond that, but none is necessary at this level.
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 combines a specific verb ('Fetch'), a resource ('full email thread'), and the relation to an inbox item. It distinguishes the tool from single-item getters like inbox.get and inbox.list by emphasizing the full thread.
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 establishes the use case: retrieving a complete thread for an inbox item. It does not explicitly name alternatives or exclusion conditions, but the intent is unambiguous enough to guide tool selection.
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 tools are largely distinct due to the domain-prefixed naming (inbox, jobs, signals, etc.) and detailed descriptions. While there is some overlap among inbox actions like acknowledge, apply_suggestion, and decline, the descriptions clarify each behavior. The signals and recommendations sub-groups also have clear boundaries, making misselection unlikely.
All tools follow a consistent pattern of domain.entity.action or domain.action (e.g., inbox.list, jobs.interviews.add, signals.recommendations.dismiss). This uniform camelCase-with-dots convention makes the set highly predictable and easy to navigate.
At 55 tools, the server far exceeds the 25-tool threshold for 'too many' as per the calibration. While the broad domain of job search management justifies numerous operations, the count is still overwhelming and could overwhelm agents or cause selection errors. Several signal-related tools could potentially be consolidated without compromising functionality.
The tool set covers the full lifecycle of job applications: inbox management (list, get, draft, send), job tracking (add, update, archive, delete), interviews (add, update, delete), offers (create, update, accept, decline, negotiation), and company signals (track, pause, recommend, block). There are no obvious missing operations for the core workflows.
