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Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral details: it explains that setting mark_read:true flags events as read, affecting subsequent calls (consuming behavior). It also mentions that the feed is persisted and describes the return structure. No contradictions 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.

Conciseness4/5

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

The description is compact (about 5 sentences) and front-loaded with the core purpose. The mention of the alternative API URL is a slight tangent but still useful context. No repetitive or filler content. A near-perfect balance of brevity and informativeness.

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?

Given 5 optional parameters, no output schema, and simple return structure, the description covers the essential aspects: what is returned, how to filter, and the side-effect of mark_read. It could mention pagination limits or ordering (e.g., newest first), but these are implicitly handled by the 'most recent' phrasing and the 'limit' param. Overall, it provides sufficient context for effective use.

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?

The input schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds extra meaning by explaining the effect of mark_read ('so the next call only shows newer ones') and clarifying that 'since' refers to fired_at time. It also gives examples for type ('sec_8k') and notes the default limit. This goes beyond the schema's bare descriptions.

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 begins with a clear action verb ('Pull') and specifies the resource ('fired events from your subscription feed'), making the tool's purpose immediately obvious. It also enumerates key return fields (source, citation_uri, raw event payload) and filter options, distinguishing it from generic listing tools.

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

Usage Guidelines3/5

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

The description provides some context by noting that polls work fine and offering an alternative access method (direct API URL), which helps decide when to use the tool. However, it does not explicitly state when to prefer this tool over sibling tools like list_subscriptions or subscribe, nor does it give clear 'when not to use' guidance.

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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TDQS

A3.8/5.0
Disambiguation3/5

Several tools form tight clusters that are easy to confuse: ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded are near-identical in routing, and the six polymarket_* tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread, bet_research) all operate on prediction markets with overlapping names and purposes. While each has a distinct job, an agent will need to read descriptions very carefully to pick the right one, especially when many are similar.

Naming Consistency2/5

Naming conventions are mixed throughout the set: many tools use verb_noun (ask_pipeworx, compare_entities, discover_tools, resolve_entity, validate_claim), but there are also noun_noun (polymarket_edges, entity_profile, bet_research), adjective_noun (deep_research, recent_alerts), and bare verbs (forget, recall, remember, subscribe). No consistent pattern emerges, making tool names harder to predict and remember.

Tool Count2/5

At 34 tools, this server is heavy and tries to serve many unrelated domains—data research, prediction markets, package registries, memory, subscriptions, and AI visibility. The prediction-markets cluster alone accounts for six highly specialized tools that could be consolidated. The scope feels bloated rather than focused, which will overwhelm agents exploring the toolset.

Completeness4/5

Each domain within the server has solid coverage: data lookups offer stable, beta, grounded, and deep-research variants; entity analysis has profile, compare, changes, and resolve; subscriptions support create/list/delete/alert-read; memory has set/get/list/delete. Minor gaps exist (e.g., no direct package search by keyword, no tool to update a subscription), but the major workflows are covered and there are no dead ends.