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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. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations indicate a write operation (readOnlyHint=false) and idempotency, but the description adds valuable context: storage as a key-value pair scoped by identifier, and retention rules ('Authenticated users get persistent memory; anonymous sessions retain memory 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.

Conciseness5/5

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

Three sentences, all high-signal. The first sentence states the core purpose, the second gives usage context, and the third covers storage details and sibling tools. No fluff.

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 2-parameter tool with no output schema, the description is highly complete: it covers what, when, how, and persistence, plus explicitly links to recall and forget. The agent has everything needed to use it correctly.

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 clear descriptions for key and value. The description adds meaning by clarifying the key-value relationship and giving examples of values to store (findings, addresses, preferences, notes), elevating it slightly above the schema baseline.

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's purpose: 'Save data the agent will need to reuse later' with a specific verb (save) and resource (data). It also distinguishes from siblings by naming the paired tools: 'Pair with recall to retrieve later, forget to delete.'

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 on when to use: 'Use when you discover something worth carrying forward' with concrete examples (ticker, address, preference, subject). It also explicitly contrasts with alternatives (recall and forget), making the choice clear.

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

A3.6/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer data questions; polymarket_arbitrage, polymarket_edges, and polymarket_edge_tracker all scan prediction markets. Despite long descriptions, an agent could easily select the wrong one, especially the currently identical ask_pipeworx and ask_pipeworx_beta.

Naming Consistency3/5

Mostly snake_case, but with inconsistent patterns: get_my_ip/lookup_ip use verb_noun, entity_profile/recent_changes are noun phrases, remember/recall/forget are bare verbs, and the polymarket_* tools share a brand-prefixed noun style. Readable but not a predictable, uniform convention.

Tool Count2/5

At 33 tools, the server is overloaded, far exceeding the 25-tool threshold for 'too many.' It combines two unrelated identities—the original ipinfo IP lookup and the massive Pipeworx data/research platform—making the toolset heavy and harder for an agent to navigate efficiently.

Completeness4/5

The tool surface provides strong coverage of the data query and research lifecycle: discovery (discover_tools, suggest_questions), entity resolution (resolve_entity), lookup (ask_pipeworx, entity_profile), verification (validate_claim, ask_pipeworx_grounded), and post-processing (search_within, recent_changes). Minor gaps exist—for example, no dedicated 'get SEC filing by accession' tool or single-purpose financials endpoint—but these are workaroundable via the routing tools.