Skip to main content
Glama

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

A4.7/5.0
Behavior5/5

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

Annotations declare readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds valuable context beyond these hints, such as scoping ('scoped by your identifier') and persistence behavior ('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?

The description is three well-structured sentences, front-loaded with the core purpose, then usage guidance, then technical context and companion tools. Every sentence adds information; no fluff or repetition.

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?

This is a simple two-parameter tool with no output schema. The description fully covers the operation's context: when to use, persistence and auth behavior, identifier scoping, and how it fits with related tools. No additional information seems necessary.

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?

The schema already provides 100% description coverage for both parameters ('Memory key' and 'Value to store'), so the baseline is 3. The description adds minor context by giving examples in the main text and explaining the key-value pair scope, but it doesn't add significant meaning beyond what the parameter descriptions already convey.

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 states a specific verb ('Save data') and resource ('data the agent will need to reuse later'), making the tool's purpose clear. It also distinguishes itself from siblings by explicitly mentioning companions: 'Pair with recall to retrieve later, forget to delete.' This clearly positions the tool within the memory family.

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?

The description provides explicit when-to-use context: 'Use when you discover something worth carrying forward' and gives concrete examples such as 'a resolved ticker, a target address, a user preference.' It also names alternatives and complementary actions ('recall', 'forget'), fulfilling the usage guidelines dimension.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

Several tool groups overlap heavily: the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) differ mainly in guarantees, and six Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) all target the same trading-concept space with fuzzy boundaries. While ArcGIS, memory, and subscription tools are distinct, an agent will frequently struggle to pick the right research or analysis tool.

Naming Consistency2/5

All names are snake_case, but the structural pattern is inconsistent. Some are verb-first (query_layer, search_datasets, validate_claim), others are noun-first or domain-prefixed (entity_profile, layer_info, polymarket_edges, recent_alerts, pipeworx_feedback). There is no predictable verb_noun convention across the set, making it hard to guess a tool's name from its function.

Tool Count2/5

At 34 tools, the set is well above the typical focused-server range, and the server name 'Arcgis Eagan' suggests a narrow GIS purpose while only 3–4 tools are actually ArcGIS-related. The remaining ~30 tools form a broad, unrelated utility collection (Pipeworx data, memory, subscriptions, trending, npm scanning), making the count feel bloated and unfocused.

Completeness2/5

For the primary ArcGIS domain, only search, layer inspection, and querying are supported — there are no create, update, delete, or editing tools, leaving obvious lifecycle gaps. Meanwhile, the Pipeworx side is over-stocked with redundant analysis tools, and the overall mix lacks a coherent coverage story for any single stated purpose.