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Glama

get_store_collection

Read-onlyIdempotent

AGENT DATASTORE — read back rows your wallet stored. Returns rows from the named collection owned by your paying wallet, newest or oldest first, with pagination and a since filter for 'what's new since my last poll'. Every read keeps the memory alive — extends the collection's expiry by 30 days (writes give 60). Output as JSON rows or CSV. ?limit=&offset=&order=asc|desc&since=ISO&format=json|csv ($0.001 per call, paid via x402)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows to return, 1-1000 (default 100)
orderNoasc or desc by insertion (default asc)
sinceNoISO timestamp — only rows created after it
formatNojson (default) or csv
offsetNoPagination offset
collectionNoCollection name in the URL path

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNo
returnedNo
collectionNo
total_rowsNo

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

The description adds value beyond annotations by detailing the expiry extension (30 days for reads, 60 for writes), cost per call, and output format options. No contradiction 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the core purpose. It packs useful information into four sentences without unnecessary detail.

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 read-only tool with 6 parameters, all described in schema, and an output schema present, the description covers all essential behavioral aspects: pagination, ordering, since filter, output format, expiry, and cost. No gaps.

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%, so baseline is 3. The description summarizes query parameters but does not add significant meaning beyond the schema. The cost and expiry details are generic, not per-parameter.

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 reads rows from a named collection owned by the wallet, with pagination and a since filter. It distinguishes from sibling tools by emphasizing read-only access and expiry extension.

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?

The description implies usage for reading stored data, but does not explicitly compare to sibling POST tools or specify when not to use. The 'AGENT DATASTORE' label provides context.

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
Disambiguation4/5

Most tools have distinct purposes, but the SEO-related tools (head_check, full_audit, site_audit, etc.) overlap in scope, potentially causing confusion despite clear descriptions.

Naming Consistency5/5

Tool names consistently follow a get_/post_/delete_ verb pattern with descriptive noun phrases (e.g., get_seo_head_check, post_store_collection), with no mixing of naming conventions.

Tool Count2/5

With 46 tools covering a wide breadth of domains (SEO, accessibility, music, crypto, linting, etc.), the count is excessive for a single server, feeling unfocused and heavy.

Completeness4/5

The tool set covers most core operations for each sub-domain, but minor gaps exist (e.g., missing update for datastore, limited music operations).