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Glama

Fmcsa

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

A3.6/5.0
Behavior1/5

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

Description claims mark_read:true flags events as read, implying a side effect, but annotations declare readOnlyHint:true and idempotentHint:true, creating a contradiction. Score set to 1 per rules.

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?

Description is concise (four sentences), front-loaded with purpose, and each sentence adds value without redundancy.

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?

Covers main functionality, return format, filters, mark_read behavior, and alternative access. Missing explicit mention of unread_only and limit, but those are in schema. No output schema but description adequately describes return structure.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. Description adds example type and ISO timestamp format but does not significantly extend beyond schema descriptions for parameters like limit and unread_only.

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, specifies return fields (source, citation_uri, raw event payload), and distinguishes it from sibling tools like list_subscriptions.

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?

Provides context on filtering by type and since, and mentions an alternative access method (GET endpoint). However, lacks explicit when-not or comparison to siblings like subscribe.

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

Many tools have distinct purposes, but there is notable overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical, as are bet_research and polymarket_edges. Detailed descriptions help, but an agent could still struggle to pick the right one.

Naming Consistency2/5

Naming conventions are mixed: snake_case (fmcsa_carrier_lookup), verb_noun (ask_pipeworx, recall), and phrases (suggest_questions, generate_llms_txt). No consistent pattern, making it harder for an agent to infer tool purpose from name alone.

Tool Count3/5

35 tools is high for a single server, but the server aggregates many domains. While each tool may serve a purpose, the count feels bloated and beyond typical scope (3-15). Some tools could be merged (e.g., the ask_pipeworx variants).

Completeness2/5

For the FMCSA domain, the four tools provide decent coverage. However, the server includes many tools for other domains (e.g., prediction markets, company profiles) without full lifecycle support (e.g., only lookup, no create/update). The set feels like a random collection rather than a coherent domain.

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