Skip to main content
Glama

Utah Open Data

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

A4.3/5.0
Behavior4/5

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

Annotations indicate readOnly, idempotent, openWorld, and non-destructive. The description adds behavioral details beyond annotations, such as the mark_read parameter affecting subsequent results (flagging events as read so next call shows only newer ones) and the return format including source and citation_uri.

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 three sentences long, front-loaded with the main purpose. It efficiently packs in details about return fields, filtering, and the mark_read behavior without being verbose or redundant.

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 no output schema, the description adequately explains return values (source, citation_uri, raw event payload) and mentions an alternative feed. All optional parameters are addressed, and the tool's behavior with mark_read is clarified, making it complete for an agent to use correctly.

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 all 5 parameters with descriptions, but the tool description adds practical context: examples like 'sec_8k' for type, explanation of mark_read, and clarification that since is an ISO timestamp. This enhances understanding beyond the schema alone.

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 pulls fired events from a subscription feed and returns recent alerts with specific fields (source, citation_uri, raw payload). It distinguishes itself from sibling tools like list_subscriptions by focusing on event retrieval rather than subscription management.

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 how to use the tool (filter by type, since, mark_read, unread_only) and mentions that polling works fine. It also provides an alternative endpoint for scripts/dashboards, offering usage context. However, it does not explicitly state when not to use this tool versus alternatives.

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

All Utah Open Data 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

A3.8/5.0
Disambiguation2/5

The toolset contains several near-duplicate clusters: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route the same kinds of questions, and the six polymarket tools have heavily overlapping scopes. An agent would frequently struggle to pick the right variant despite the detailed descriptions.

Naming Consistency4/5

Names consistently use lowercase snake_case with a verb-first or domain-prefixed pattern (ask_pipeworx, resolve_entity, validate_claim, polymarket_arbitrage). Minor deviations like bare nouns (datasets, metadata) are acceptable but not perfectly uniform.

Tool Count2/5

34 tools is far beyond what a Utah Open Data server needs; only 3 tools actually relate to the named domain. The rest form a sprawling general-purpose Pipeworx/prediction-market platform, making the surface feel bloated for its stated purpose.

Completeness3/5

For the actual Utah Open Data catalog, datasets/query/metadata is a complete read-only surface. But for the broader Pipeworx functionality the set actually delivers, there are odd gaps (no account management beyond subscriptions) and many irrelevant tools, so overall coverage is uneven.

Resources