Skip to main content
Glama

Data Seattle

by io.github.pipeworx-io

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

A4.8/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds important behavioral details: setting mark_read:true flags events as read (a non-destructive side effect), and mentions that the feed is persisted and accessible via a GET endpoint. No contradictions.

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 well-structured sentences, each adding value. Front-loaded with purpose, then details on return fields and parameters, then usage guidance. No unnecessary words.

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

Completeness5/5

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

Despite no output schema, the description sufficiently explains return fields (source, citation_uri, raw payload) and provides context on polling and alternative access. For a read-only tool with 5 optional parameters, this is complete and self-contained.

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

Parameters5/5

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

Schema coverage is 100%, and the description adds meaning to each parameter: type filter, limit max, since ISO timestamp, mark_read flag behavior (flags events read in same call), unread_only filter. This goes beyond the schema's basic 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 states 'Pull fired events from your subscription feed' with specific verb and resource. It distinguishes itself from siblings like list_subscriptions and recall by focusing on fired alerts and providing details on return fields (source, citation_uri, raw payload) and filtering options.

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 explains when to use this tool (retrieving fired events from subscription feed) and notes that 'Polls work fine' and an alternative GET endpoint exists. It doesn't explicitly state when not to use it, but the guidance is clear and practical.

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

All Data Seattle toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation3/5

Many tools have distinct purposes, but the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the prediction market tools (bet_research, polymarket_edges, polymarket_arbitrage) can cause confusion due to overlapping functionality. Some tools like 'seattle_recent' are vague.

Naming Consistency4/5

Most tools follow a consistent verb_noun or noun_verb pattern (e.g., validate_claim, resolve_entity). However, a few like 'seattle_recent' and 'pipeworx_trending' deviate slightly, and 'recent_alerts' mixes noun_verb.

Tool Count2/5

34 tools is excessive for a single server, covering data retrieval, prediction markets, Seattle data, memory, subscriptions, and utility. The broad scope feels bloated and overwhelming, making it hard for agents to find the right tool.

Completeness4/5

The server covers a wide array of domains with good depth in data retrieval and prediction markets. Minor gaps exist (e.g., Seattle tools limited to four datasets, no other city data), but overall it addresses most use cases its tools suggest.

Resources