Skip to main content
Glama

Attom

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

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

  1. Added

TDQS

A5/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint true and destructiveHint false. The description adds significant behavioral context: fans out to multiple sources in parallel, fallback from GDELT to GNews, soft-fail for USPTO, and describes output format (changes grouped by source, total_changes, pipeworx:// URIs). No contradictions noted.

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?

The description is structured with front-loaded example queries, then details on sources, parameters, and output. Every sentence adds value; there is no redundancy or filler. It efficiently conveys all necessary information.

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?

Given the complexity (multiple data sources, fallback logic, output format) and lack of output schema, the description thoroughly covers behavior and return structure. It also correctly contextualizes the tool among siblings by pointing to entity_profile for static needs.

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%. The description elaborates on each parameter: 'type' explains it's only 'company', 'since' gives ISO date and relative shorthand examples ('7d', '30d', '3m', '1y') with recommendation ('Use 30d or 1m for typical monitoring'), and 'value' explains ticker or zero-padded CIK. This adds meaning beyond the schema.

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 explicitly states the tool's purpose: 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It gives example queries like 'latest on Y' and lists sources (SEC EDGAR, GDELT/GNews, USPTO), clearly distinguishing from sibling 'entity_profile' by directing users to use that for static profiles.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance with natural language examples ('What's new with X', 'updates on Acme') and specifies when not to use it: 'Use entity_profile instead when you want the static profile...' This clearly differentiates between the two tools.

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

All Attom 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

A3.7/5.0
Disambiguation2/5

Several tools are nearly indistinguishable without deep reading: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all route the same universal query, and the beta currently behaves identically. The prediction-market clister (polymarket_arbitrage, pollymarket_edges, pollymarket_edge_tracker, pollymarket_fill_risk, pollymarket_kalshi_spread) and value-estimation tools (attom_avm, attom_assessment, attom_rental_avm) have fuzzy boundaries that will cause misselection.

Naming Consistency4/5

The vast majority of tools follow a consistent lower_snake-case convention with clear prefixes (attom_*, polymarket_*, pipeworx_*) and verb-noun forms (generate_llms_txt, list_subscriptions, resolve_entity). Minor deviations exist like the bare memory verbs remember, recall, forget and domain-noun names entity_profile, bet_research, but the overall pattern is predictable and readable.

Tool Count2/5

39 tools is well above the comfortable 3-15 range and signals scope creep: the server bundles real-estate, prediction markets, company research, memory, subscriptions, web utilities, and a universal data router. Many of these could be grouped into a smaller number of composite tools, as the descriptions themselves already suggest (e.g. ask_pipeworx as the default entry point).

Completeness3/5

Coverage is deep for prediction markets, company financials, and real-estate, with complete memory and subscription lifecycles (remember/recall/forgeet, subscribe/list/unsubscribe/recent_alerts). However, many advertised domains (weather, clinical trials, news, government records) are only reachable through the generic ask_pipeworx router rather than dedicated tools, and scan_dependency is npm-only, leaving obvious gaps for other ecosystems.

Resources