Skip to main content
Glama

Data Piercecounty

by io.github.pipeworx-io

Remember

remember
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 indicate idempotent and non-destructive. Description adds key behavioral context: scoped by identifier, persistent vs 24-hour retention, and that it's a key-value store. No contradictions with annotations.

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?

Four sentences, each carrying essential information. Purpose is front-loaded. No redundancy or filler.

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 simple params (2 required strings, no output schema), description covers purpose, usage, behavioral nuances, and pairing with siblings. Completely adequate for effective tool selection.

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% with adequate descriptions for both key and value. Description provides examples but adds minimal extra meaning beyond the schema. Baseline 3 is appropriate.

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?

Description uses specific verbs ('save', 'reuse later') and resource ('key-value pair stored by identifier'). Provides concrete examples (ticker, address, preference). Clearly distinguishes from sibling tools like 'recall' and 'forget'.

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?

Explicitly states when to use: 'when you discover something worth carrying forward'. Mentions pairing with recall and forget. Notes scope differences between authenticated and anonymous sessions.

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

All Data Piercecounty 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

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions differentiating them. Potential overlap between ask_pipeworx and deep_research is addressed in descriptions (single vs. multi-faceted queries). Similar separation exists among prediction market tools and memory management functions.

Naming Consistency3/5

Naming conventions are mixed: some use snake_case verbs (ask_pipeworx), others are noun phrases (recent_alerts). Prefixes like pipeworx_ and polymarket_ provide grouping, but the inconsistent verb/noun structure and occasional camelCase break a predictable pattern.

Tool Count3/5

33 tools is high, but the server covers a broad domain (data queries, prediction markets, memory, subscriptions). While the server name suggests Pierce County focus, only 3 tools are specific to it; the rest are general-purpose Pipeworx tools. The count feels slightly bloated but has logical subgroups.

Completeness2/5

For the implied domain (Pierce County data), only 3 tools (datasets, metadata, query) are provided, missing common operations like listing all datasets, or data management. The broader Pipeworx functionality is extensive, but the server's name suggests a narrower scope, leaving significant gaps.

Resources