messages_outboundList outbound messages sent through the Postmark server with optional filters (recipient, from, tag, status, fromdate, todate); returns message summaries with status and timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| Messages | No | ||
| TotalCount | No | Total number of messages |
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, destructiveHint=false, and idempotentHint=true. Description adds that it returns summaries with status and timestamps, but doesn't disclose pagination, rate limits, or filter value formats. No contradiction with 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?
Single concise sentence, front-loaded with verb and resource, then filters and return info. No wasted words.
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?
Given strong annotations, output schema, and read-only nature, the description covers core functionality. However, it doesn't distinguish from message_outbound_detail/dump or explain filter formats, so slightly less complete than ideal.
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 has zero properties, but description lists six optional filters (recipient, from, tag, status, fromdate, todate), giving names the schema lacks. Baseline for 0 params is 4; description adds value but doesn't explain value formats (e.g., date format).
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?
Description clearly states the verb ('List') and resource ('outbound messages sent through the Postmark server'), with specific optional filters. It distinguishes from sibling tools like message_outbound_detail (which implies a single message's detail) and message_outbound_dump (raw data).
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?
Provides clear context: for listing summaries with filters. Does not explicitly name alternatives or exclusions, but the scope is apparent from sibling names and the phrase 'returns message summaries' implies it's for summary-level viewing.
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 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.
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.
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.
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.