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)

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations idempotentHint=true and destructiveHint=false are consistent with description. Description adds context about memory retention for anonymous vs authenticated users, enhancing transparency.

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 informative and front-loaded with purpose. Every sentence adds value, though it could be slightly more concise. 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 no output schema, the description is complete. It covers retention, scoping, and pairing with related tools, with no missing critical information.

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 descriptions already cover both parameters (key, value) at 100% coverage. Description adds meaningful examples and context, such as key naming conventions and value types.

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 saves data for reuse across conversations/sessions, with specific examples like tickers, addresses, and preferences. It distinguishes from sibling tools recall and forget.

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 states when to use: when discovering something worth carrying forward. Also mentions pairing with recall and forget, and provides scoping and retention details.

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

B3.3/5.0
Disambiguation1/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all answer questions or discover data via the same routing engine, with ask_pipeworx_beta explicitly stated to be identical to ask_pipeworx. Polymarket tools (arbitrage, edges, edge_tracker, fill_risk) also blur together, and ai_visibility_check overlaps with scan_competitor_ai_presence.

Naming Consistency2/5

Some clusters are consistent (chargebee_list_*/chargebee_get_*, polymarket_*, pipeworx_*), but the set mixes snake_case with varying verb styles and many unprefixed tools (remember, recall, forget, subscribe, unsubscribe, validate_claim). The 5 Chargebee tools use a clean prefix while the other 31 tools follow several different conventions, making the overall pattern unpredictable.

Tool Count2/5

36 tools is excessively heavy for a server named Chargebee, especially since only 5 tools actually relate to Chargebee. The remaining 31 tools form a broad Pipeworx/prediction-market/utility toolkit that has little connection to the server's apparent billing purpose, making the count feel bloated and unfocused.

Completeness1/5

The Chargebee-specific surface is severely incomplete: it only supports reading customers, subscriptions, and invoices, with no create, update, delete, payment, dunning, coupon, or plan-management operations. The rest of the tools belong to unrelated domains, so the set as a whole has no coherent lifecycle coverage and would leave agents unable to perform even basic Chargebee management tasks.