Skip to main content
Glama

Google_sheets

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)

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare idempotentHint and destructiveHint, but description adds valuable context: data is scoped by identifier, authenticated users get persistent memory, anonymous sessions retain for 24 hours. 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?

Description is moderately concise; front-loads the main purpose. Each sentence adds value, though some minor redundancy ('across this conversation or across sessions') could be tightened. Overall 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?

For a simple key-value store with 2 parameters and no output schema, the description is complete. It covers purpose, usage timing, pairing with siblings, and persistence behavior. No gaps given complexity.

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% and schema descriptions are adequate. Description adds example key patterns ('subject_property', 'target_ticker') which provide mild additional context, but does not significantly enhance parameter understanding beyond 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?

Clearly states the tool saves data for reuse across conversations/sessions. Distinguishes from siblings 'recall' and 'forget' by mentioning pairing. Specific verb 'save' with resource 'key-value pair'.

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 says 'Use when you discover something worth carrying forward' and advises pairing with 'recall' to retrieve and 'forget' to delete. 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.

All Google_sheets 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

B3.1/5.0
Disambiguation2/5

Several tools are nearly identical: ask_pipeworx and ask_pipeworx_beta are explicitly the same, and ask_pipeworx, ask_pipeworx_grounded, and deep_research all serve overlapping research/query purposes. discover_tools and suggest_questions both act as discovery entry points, while the five polymarket tools differentiate primarily through intricate details that are easy to confuse.

Naming Consistency2/5

Naming conventions are mixed across the set: verb_noun (ask_pipeworx, resolve_entity, validate_claim), noun_verb (sheets_append, sheets_create), noun_noun (polymarket_arbitrage, entity_profile), and bare verbs (forget, recall, subscribe). The sheets tools are internally consistent but the broader collection has no uniform pattern, with awkward names like pipeworx_trending and search_within.

Tool Count2/5

With 36 tools, the server exceeds the 25-tool threshold for 'too many'. The Google Sheets portion accounts for only 5 tools, while the majority are highly specialized Pipeworx and Polymarket tools that could be consolidated or dramatically reduced. The count feels inflated relative to the advertised 'Google_sheets' server name and its actual core purpose.

Completeness2/5

For a server named Google_sheets, the essential operations exist (create, read, write, append, list structure), but there is no delete/clear range tool and no way to add a new sheet to an existing spreadsheet. For the broader data/research scope, important lifecycles are missing (e.g., no direct way to write Pipeworx results into Sheets, no update for subscriptions, only cancel). The set falls short of fully covering either domain.

Resources