sendgrid_add_or_update_contactsUPSERTS marketing contacts (creates new ones, updates existing ones by email) and optionally adds them to lists. This is an ASYNC job — returns { job_id } you can poll. SendGrid: PUT /v3/marketing/contacts.
| Name | Required | Description | Default |
|---|---|---|---|
| contacts | Yes | Contacts to add or update (each needs an `email`; custom fields pass through). | |
| list_ids | No | List ids to add these contacts to. |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only give destructiveHint=true, so the description carries most of the burden and does add real value: it discloses the async job semantics and the { job_id } you must poll. It also clarifies the upsert/match-by-email behavior, which matters for a destructive write. It stops short of describing auth/permission needs or rate limits.
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 tight sentences front-load the upsert semantics and the async/polling behavior before the API mapping reference. Every clause earns its place.
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?
There is no output schema, but the description compensates by explaining the async return value ({ job_id }) and that it must be polled. Combined with the destructiveHint annotation, an agent has enough to invoke it correctly; only deeper operational details (auth scopes, rate limits) are absent.
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%, so the schema already documents `contacts`, nested custom-field pass-through, and `list_ids`. The description only restates the email-as-identifier and optional list behavior, adding no syntax or format detail beyond the schema — baseline 3 applies.
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?
States a precise verb+resource ('UPSERTS marketing contacts') and immediately explains both branches (creates new, updates existing by email) plus the optional list-add behavior. An agent can distinguish it from read-oriented siblings like sendgrid_search_contacts_by_email and sendgrid_list_marketing_lists without opening the schema.
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 when to use it (adding or updating contacts, optionally to lists), but never states when NOT to use it or names an alternative for read/lookup cases among its siblings. Usage is inferred rather than spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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