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Glama

Epa Echo

by io.github.pipeworx-io

Remember

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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

A4.9/5.0
Behavior5/5

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

Annotations indicate idempotent, non-destructive. Description adds details: 'Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours.' No contradiction.

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?

Well-structured: first sentence states purpose, then usage condition, then behavioral details. Every sentence adds value; no wasted words.

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 no output schema, the description comprehensively covers storage behavior, scoping, persistence, and pairing with sibling tools. Complete for a write operation.

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 has 100% coverage with descriptions for both parameters. Description adds context beyond schema (usage context, scoping, pairing) but does not detail parameter values beyond examples.

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 'Save data the agent will need to reuse later' and specifies the resource (data) and verb (save). It distinguishes from siblings 'recall' and 'forget' by mentioning them.

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?

Explicit guidance: 'Use when you discover something worth carrying forward... so you don't have to look it up again.' Also explains persistence differences for authenticated vs anonymous sessions.

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

A3.9/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded form a tight cluster, and the beta variant is explicitly identical to ask_pipeworx today. Several meta-tools like discover_tools, suggest_questions, and deep_research also overlap in discovery-oriented usage, so an agent must read carefully to pick the right one.

Naming Consistency3/5

Names are uniformly lowercase with underscores and mostly descriptive, but the conventions are mixed: verb_noun tools like validate_claim and list_subscriptions sit alongside noun_phrase tools like entity_profile and polymarket_arbitrage, plus bare verbs like remember and subscribe. It is readable but not a single predictable pattern.

Tool Count2/5

36 tools is well above the 25+ threshold, and the surface spans unrelated domains: EPA ECHO data, general Pipeworx research, Polymarket betting, memory, npm scanning, and AI visibility checks. For a server named 'Epa Echo', most tools feel out of scope and the collection seems like several separate servers merged together.

Completeness4/5

The EPA ECHO subset provides a solid facility-search, violations, compliance-history, and enforcement-action lifecycle. The broader Pipeworx surface also covers lookups, grounded answers, deep research, entity profiling, subscriptions, and memory, with only minor workaround-level gaps such as no dedicated ECHO permit/emissions detail tool.

Resources