nylas_get_messageGet a single email message by id. Nylas v3: GET /v3/grants/{grant_id}/messages/{message_id}.
| Name | Required | Description | Default |
|---|---|---|---|
| grant_id | No | Connected-account grant id. Overrides NYLAS_GRANT_ID for this call. | |
| message_id | Yes | The message id to fetch. |
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=true, so the description's disclosure of the API endpoint adds context but does not significantly extend beyond that. The description does not detail behavioral aspects like authentication requirements or error scenarios, but with annotations present, the burden is reduced.
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 with two sentences, no redundant words, and front-loads the core purpose. Every sentence adds necessary context.
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 description does not explain the return value (no output schema) but given the tool's simplicity and read-only nature, it is minimally adequate. More detail on expected response format would improve completeness.
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?
Both parameters are fully described in the schema (100% coverage). The description's mention of the endpoint path hints at the role of grant_id but adds no new semantic meaning beyond the existing schema descriptions.
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 retrieves a single email message by ID, specifying the verb 'Get' and resource 'single email message'. It distinguishes from sibling tools like nylas_list_messages (list) and nylas_send_message (send) by focusing on a single message retrieval.
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 implies usage when an email ID is known but provides no explicit guidance on when to use this tool versus alternatives like nylas_list_messages or nylas_get_contact. No conditions or exclusions are mentioned.
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.
Each tool targets a distinct resource and action: create vs list vs get for specific entities like draft, event, calendar, contact, grant, message, folder. There is no overlap, as even similar verbs like 'list' are paired with unique nouns. Agents can easily select the correct tool.
All tool names follow a uniform 'nylas_verb_noun' pattern using snake_case, with clear and predictable verbs (create, get, list, send) and nouns (draft, event, calendar, etc.). The naming is fully consistent across all 15 tools.
With 15 tools, the set is well-scoped for a Nylas integration covering email, calendar, and contacts. Each tool serves a clear purpose without redundancy, and the count falls comfortably within the ideal range of 3-15 tools.
The tool set covers reading and limited creation (drafts, events) but lacks update and delete operations for all entities, as well as create for contacts. This leaves notable gaps for full lifecycle management, though core workflows like listing and fetching are present.