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Glama

Pangaea

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true and readOnlyHint=false. The description adds valuable context about scoping by identifier, persistence differences between authenticated and anonymous sessions, and the key-value nature of storage. It does not mention overwrite behavior explicitly, but the idempotent hint covers that.

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 concise and well-structured, with the main purpose in the first sentence and supporting details following. Every sentence earns its place, providing practical examples and usage context without unnecessary fluff.

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?

For a simple 2-parameter tool with no output schema, the description covers purpose, usage, persistence behavior, and pairing with sibling tools. It is complete and leaves no significant gaps for the agent to select and invoke the tool.

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 description coverage is 100%, so the parameters are fully documented in the schema. The description reinforces the key-value concept but does not add new parameter-specific details beyond what the schema already provides. Baseline 3 applies.

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 saves data for later reuse, specifying the action ('Save data') and the resource ('key-value pair'). It distinguishes itself from siblings like recall and forget, which are explicitly mentioned as complementary tools.

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?

It provides explicit when-to-use guidance ('Use when you discover something worth carrying forward') and names alternatives (recall, forget) for retrieval and deletion. This gives clear context for when to choose this tool over others.

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

All Pangaea toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded and validate_claim both perform claim verification, and polymarket_edges and polymarket_arbitrage both surface trading opportunities. While descriptions are detailed, the boundaries are fuzzy and agents could easily select the wrong tool.

Naming Consistency3/5

Naming mixes verb-first (search, subscribe, recall, validate_claim) with noun-first (dataset, facets, recent, entity_profile) conventions, and some names are just adjectives or nouns. Consistent prefixed groups exist (polymarket_*, ask_pipeworx_*), but the overall style is inconsistent and the server name 'Pangaea' doesn't align with the dominant 'pipeworx' prefix.

Tool Count2/5

36 tools is excessive for a coherent set, especially given the server bundles unrelated domains (earth science, general data research, prediction markets, memory, utilities). Several tools are redundant (e.g., ask_pipeworx_beta duplicates ask_pipeworx), and many are niche (ai_visibility_check, generate_llms_txt, scan_dependency) that don't fit the apparent primary purpose.

Completeness3/5

The PANGAEA dataset surface covers search, retrieval by ID/DOI, recent, and facets, but lacks export or citation tools. The Pipeworx research tools are broad, but prediction market access has no simple market-price query (only analysis-oriented tools), and there are notable gaps in lifecycle coverage for some subdomains.

Resources