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.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and idempotentHint=true. The description confirms deletion and adds a privacy rationale, but it does not disclose additional behavioral details such as irreversibility or handling of nonexistent keys beyond what the annotations imply. It is consistent, not contradictory.
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 three short sentences, front-loaded with the primary action, and every sentence provides useful context. 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?
For a simple single-parameter delete tool with annotations covering destructiveness and idempotence, the description is adequate. It covers purpose, usage timing, and relationship to siblings. It could mention behavior on missing keys or explicit irreversibility, but annotations already hint at these, so it is nearly complete.
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 schema already documents the only parameter 'key' with the description 'Memory key to delete' (100% coverage). The description's 'by key' adds no extra meaning beyond what the schema provides, so baseline 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 clearly states the verb and resource: 'Delete a previously stored memory by key.' This is specific and distinguishes it from sibling tools like remember and recall, which handle storage and retrieval.
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 says 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 mentions pairing with remember and recall, providing guidance on how it fits into the tool ecosystem.
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.
Several tools occupy nearly the same niche: ask_pipeworx_beta is explicitly an identical duplicate of ask_pipeworx when no experiment is active, and ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim all overlap as question-answering entry points. Other families like entity_profile vs compare_entities vs recent_changes and ai_visibility_check vs scan_competitor_ai_presence also blur together despite long disambiguating descriptions.
All tool names use a clean, readable snake_case style, and there are strong prefix families like ask_pipeworx, polymarket_, list_, and scan_. However, the set is not uniformly verb_noun: entity_profile, deep_research, recent_alerts, pipeworx_trending, and several others are noun phrases rather than actions, so the pattern is mostly consistent but not strict.
34 tools is well beyond the 25+ threshold where a server starts feeling bloated, and the server name 'Space Feeds' suggests a narrow niche while most of the surface is a general data research, prediction-market, memory, and subscription platform. Each tool may be useful, but as a set the scope is sprawling rather than focused.
The major workflows have good lifecycle coverage: data lookup and grounded verification, entity resolution and profiling, prediction-market analysis, memory (remember/recall/forget), subscriptions (subscribe/list/unsubscribe/recent_alerts), and feed reading (list/read/fetch) are all represented. Minor gaps include a direct pipeworx:// citation reader and feed curation or management operations, but agents can work around those.