Skip to main content
Glama

Quotable

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

A4.9/5.0
Behavior5/5

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

Discloses persistence behavior beyond annotations: authenticated users get persistent memory, anonymous sessions retain for 24 hours. Also implies overwriting (idempotent). 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.

Conciseness5/5

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

Five sentences, front-loaded with purpose, then usage guidance, then behavioral detail. No redundancy or filler. Every sentence adds value.

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 rich annotations and schema, description fully covers purpose, usage, and behavioral traits. No missing information needed for tool selection or invocation.

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 coverage is 100% with inline descriptions for key and value. Description adds context by stating 'stored as a key-value pair' and providing examples, which reinforces parameter roles 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?

Description clearly states 'Save data the agent will need to reuse later' with specific verb (save), resource (memory), and context (across sessions). Distinguishes from siblings recall and forget by mentioning them explicitly.

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?

Provides explicit usage context: 'when you discover something worth carrying forward' with concrete examples (ticker, address, preference). Also advises pairing with recall/forget for retrieval/deletion.

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

All Quotable 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

A3.7/5.0
Disambiguation2/5

The ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) is highly overlapping—two of them are explicitly identical right now—and the six polymarket_* tools plus bet_research create unclear boundaries between prediction-market analysis tools. Company-focused tools (entity_profile, compare_entities, recent_changes, resolve_entity) also partially overlap in what they fetch, making tool selection error-prone.

Naming Consistency4/5

Most tool names follow a clear snake_case pattern with descriptive verbs (search_quotes, resolve_entity, validate_claim, subscribe, unsubscribe). There is good use of family prefixes like polymarket_* and pipeworx_*, though the Pipeworx family mixes prefix and suffix placement (ask_pipeworx vs. pipeworx_feedback), which is a minor inconsistency.

Tool Count2/5

35 tools is far too many for a server named 'Quotable', especially since only 4 tools (get_authors, list_tags, random_quote, search_quotes) relate to quotes. The rest span data lookup, prediction markets, memory, subscriptions, AI visibility, and dependency scanning—an extremely broad, unfocused scope that overwhelms the apparent purpose.

Completeness3/5

The quote-related surface is minimal but functional (random, search, authors, tags), though missing obvious operations like get_quote_by_id. The data-lookup and prediction-market domains are thoroughly covered with grounding, research, arbitrage, and fill-risk tools, so the broader set is complete—but it does not serve the server's stated identity as a quotes provider.

Resources