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, so the description carries a lighter burden. It adds useful context by framing the deletion as clearing 'previously stored' memory and 'sensitive data', implying permanence and a privacy rationale. It does not contradict 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?
The description is two compact sentences: the first states the core operation, the second gives usage conditions and sibling pairings. Every sentence earns its place with no wasted words.
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?
Given a single well-documented parameter, strong annotations (destructive, idempotent), and no output schema, the description fully covers the what, when, and how it relates to other tools. There are no significant gaps in context for an agent to invoke it correctly.
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?
The input schema has 100% coverage: the key parameter is described as 'Memory key to delete'. The description's phrase 'by key' adds no additional meaning beyond the schema, so the baseline of 3 is appropriate.
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 opens with 'Delete a previously stored memory by key' — a specific verb and resource that clearly states the operation. It distinguishes from siblings like remember (store) and recall (retrieve) by focusing on deletion, so the purpose is unmistakable.
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?
The description explicitly states when to use the tool: 'Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier.' It also names companion tools ('Pair with remember and recall'), providing direct guidance relative to 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.
Each tool has a clearly distinct purpose and description, with no overlap. For example, ask_pipeworx vs ask_pipeworx_grounded are differentiated by hallucination resistance, and all Polymarket tools have unique roles.
Tool names follow a mostly consistent snake_case pattern with descriptive verb_noun structures (e.g., ask_pipeworx, get_intensity, resolve_entity). Minor deviations like generate_llms_txt and pipeworx_feedback do not cause confusion.
33 tools is high for a single server, covering many domains (Pipeworx, Polymarket, electricity, memory, npm). While well-organized, the broad scope may feel bloated for a focused use case.
Within each subdomain, the tool surface is complete: Pipeworx has query, research, entities, subscriptions; Polymarket has arbitrage, edges, fill risk; electricity has mix and intensity. Only minor gaps exist (e.g., missing PyPI support in scan_dependency).