forgetDelete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key to delete |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "key": "user_research_topic"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide destructiveHint=true and idempotentHint=true; the description adds context about deleting previously saved memories and the scenario of clearing sensitive data, without contradicting annotations. It does not detail idempotent behavior on missing keys, but that is covered by annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with action first; includes purpose, usage, and sibling pairing without redundancy. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter delete tool with full schema coverage and annotations, the description fully covers what the tool does, when to use it, and its relation to siblings. No output schema is needed for this simple operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with description 'Memory key to delete'; the tool description only echoes 'by key', adding no additional semantic detail beyond schema. Baseline 3 is appropriate since the schema fully documents the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Delete' and resource 'previously stored memory by key', clearly distinguishing it from sibling tools like remember and recall. It is unambiguous about the action and target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use ('context is stale, task is done, sensitive data') and names complementary tools ('Pair with remember and recall'), giving clear selection guidance and alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same data sources, and the Polymarket family (polymarket_edges, polymarket_edge_tracker, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread) has blurred boundaries. Agents would struggle to pick the right one without reading every description carefully.
Naming is mostly snake_case but follows no consistent verb_noun pattern. Verbs vary widely (ask_, get_, list_, search_, compare_, scan_, validate_, remember, recall, forget, subscribe, unsubscribe, discover, generate, resolve, suggest) and many tools are bare nouns (entity_profile, recent_alerts, polymarket_edges). The inconsistency makes the set feel ad hoc.
34 tools is on the heavy side, and the count is inflated by many near-duplicate data-router and prediction-market tools. The server is named 'iconify' yet only 3 of 34 tools actually relate to icons, indicating poor scoping for the stated purpose.
For the icon domain, the surface is minimal (list, search, get) with no create/update/delete. For the broader data/prediction-market domain, there are significant gaps in lifecycle coverage (e.g., subscriptions have create/cancel but no pause/resume, and the memory tools lack namespacing). The mixed focus means no single domain is fully covered.