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Glama

Defillama

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

A4.8/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent, openWorld), the description reveals multi-source fan-out, fallback logic (GDELT→GNews), and a soft-fail condition (USPTO PatentsView sunset). It also describes the return structure (changes[], total_changes, citation URIs). 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?

The description is a single, well-structured paragraph that front-loads example queries and efficiently covers purpose, sources, parameters, and alternative tool. No redundant or unnecessary sentences.

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?

The description adequately covers return structure and key behaviors (source fallback, soft-fail). However, it omits details on pagination, maximum result count, or potential timeouts, which would be helpful for a data-fetching tool. Annotations somewhat compensate (openWorldHint implies no strict limits).

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?

Schema coverage is 100% with clear descriptions for all three parameters. The description adds value by explaining the 'since' parameter's dual date formats and the purpose of 'type' and 'value' in context. Slight deduction because schema already does most of the work.

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 provides a change feed for a company within a time window, aggregating from multiple sources (SEC, GDELT/GNews, USPTO). It distinguishes itself from the sibling entity_profile by stating when to use the latter instead.

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 offers explicit guidance: example queries ("What's new with X"), supported date formats (ISO or relative), source fallback behavior, and a direct reference to entity_profile for static profile needs.

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

A4/5.0
Disambiguation4/5

Most tools have distinct purposes, but the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) could cause confusion despite detailed descriptions. Other tools like defi_chain_tvl and defi_tvl_protocols are well differentiated.

Naming Consistency3/5

Tool names use a mix of snake_case and descriptive phrases (e.g., defi_chain_tvl vs resolve_entity). No consistent verb_noun pattern; some are imperative verbs (subscribe, forget), others are nouns (bet_research). Still readable but not uniform.

Tool Count3/5

37 tools is high for a single server, but the server covers an unusually broad domain (DeFi, SEC, FDA, economics, prediction markets, etc.). Each tool has a specific role, but the meta-tools (discover_tools, suggest_questions) add to the count. Slightly over-scoped but justifiable.

Completeness4/5

The tool set covers a wide range of data sources and operations: lookup, comparison, monitoring, feedback, and meta-discovery. Minor gaps exist (e.g., no direct DeFi transaction tools, no batch processing), but for a data-gathering server it is fairly complete.

Resources