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Glama

Quran

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?

Adds behavioral context beyond annotations: storage scoped by identifier, persistence difference for authenticated vs anonymous users. Annotations already indicate idempotent and non-destructive. 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?

Four concise sentences, front-loaded with main purpose. No wasted words. Well-structured.

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?

Complete for a simple key-value store tool. Covers when to use, how it works, pairing with other tools. No output schema needed. All relevant context provided.

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 already describes both parameters (100% coverage). Description adds example key patterns and value types, adding 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?

Description clearly states the tool's purpose: 'Save data the agent will need to reuse later'. It specifies the resource (key-value memory) and the 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 Guidelines4/5

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

Explicitly says when to use: 'when you discover something worth carrying forward'. Provides examples. Mentions alternatives: 'Pair with recall to retrieve later, forget to delete'. Does not explicitly state when not to use, but context is clear.

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

All Quran toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Several tools have overlapping mandates: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all perform routed research, while ai_visibility_check and scan_competitor_ai_presence overlap, and the Polymarket tools aside from bet_research are closely related. The descriptions are detailed, but an agent could easily select the wrong research or data-retrieval tool.

Naming Consistency4/5

The set largely follows a clear snake_case verb_noun pattern (get_ayah, list_surahs, search_quran, resolve_entity, validate_claim). There are minor deviations like entity_profile, recent_alerts, and pipeworx_trending, but no mixed casing or chaotic naming.

Tool Count2/5

35 tools is far too many for a server named 'Quran': only four tools actually serve Quran lookups, while the other 31 are a general-purpose data, prediction-market, and memory suite. The count feels like two or three unrelated servers merged into one, which does not match the stated purpose.

Completeness3/5

The four Quran tools cover the core list/get/search operations reasonably well, so that subdomain has no major dead ends. However, as a Quran server the surface is diluted by unrelated tools, and as a general-purpose server the mixed scope makes it hard to call the tool set complete for any single clear domain.

Resources