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Postmark

by io.github.pipeworx-io

Send Batch

send_batch
Idempotent

Send a batch of up to 500 transactional emails in one call to the Postmark delivery API (api.postmarkapp.com/email/batch), passing an array of messages in Postmark field form (From, To, Subject, HtmlBody, TextBody, Tag, MessageStream) and a Postmark server token. Returns one result per message with its MessageID, recipient, and error code. Use it for bulk receipts, digests, or notification sends through Postmark.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of items returned.
itemsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds key behavioral details beyond the annotations: the batch size limit (500), the required Postmark server token, and the response format (per-message MessageID, recipient, error code). This meaningfully informs the agent about side effects and partial failures, without contradicting the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences pack the action, target API, payload structure, response details, and use-case guidance with no redundancy. Every sentence adds value and the key action is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is very complete for a single-parameter tool: it covers purpose, payload format, response semantics, and use cases, and an output schema exists. The only minor gap is the token mention not reflected in the schema, which could cause slight confusion, but overall it is thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema only defines 'emails' as an array with no item structure. The description compensates by enumerating the Postmark message fields (From, To, Subject, etc.) and the token requirement. However, the token is not in the schema, so the agent may be unsure how to supply it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool sends a batch of up to 500 transactional emails in one call to the Postmark delivery API, with a specific endpoint and message field structure. This distinguishes it from the sibling 'send' tool for single emails.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly recommends using this tool for bulk receipts, digests, or notification sends, giving clear context. However, it does not explicitly mention when not to use it or name the alternative 'send' tool for single emails.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Postmark toolsInspect
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TDQS

B3/5.0
Disambiguation2/5

The tool set mixes multiple domains (Postmark email, Pipeworx data queries, Polymarket betting, memory utilities) with several overlapping tools. ask_pipeworx and ask_pipeworx_beta are essentially identical, send/send_batch and bounces/bounce are similar, and multiple polymarket analysis tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker) could be confused. Despite detailed descriptions, the sheer number of query and analysis tools increases the chance of misselection.

Naming Consistency3/5

All tool names use lowercase_with_underscores, so the casing is consistent. However, there is no uniform verb_noun pattern: some start with verbs (ask, send, bounce, resolve, validate), while others are noun phrases (server, bounces, recent_alerts, entity_profile). This mixed semantic structure makes it less predictable, but the names are still readable.

Tool Count2/5

41 tools is far above the typical well-scoped range of 3-15. The server combines multiple unrelated domains—email, data lookup, prediction markets, memory, and subscriptions—resulting in a heavyweight and unfocused surface. Most of the tools would be better split into separate, purpose-specific servers.

Completeness2/5

For a server named Postmark, the email side is incomplete: there is no update server configuration, message stream management, or inbound email handling. The Pipeworx data tools provide good read coverage but lack write/management operations for entities. The inclusion of unrelated tools makes the surface feel arbitrary rather than complete for any single domain.

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