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 declare destructiveHint=true and idempotentHint=true, so the safety profile is known. The description adds meaningful context by mentioning 'clear sensitive data' and 'stale context', which explains why deletion is appropriate without contradicting 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 three short sentences, front-loaded with the core action and followed by usage guidance. Each 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?
For a simple one-parameter destructive tool with strong annotations and no output schema, the description is complete. It covers what the tool does, when to use it, and how it relates to sibling tools, leaving no important gaps.
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 has 100% coverage for the single 'key' parameter, and the description's 'by key' aligns with it. However, the description provides no additional parameter-specific semantics beyond what the schema already states, so the baseline of 3 applies.
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 a specific verb ('Delete') and resource ('previously stored memory by key'), immediately clarifying the tool's action. It also distinguishes itself from sibling tools by pairing with 'remember and recall', making its place in the memory toolset clear.
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: 'when context is stale, the task is done, or you want to clear sensitive data'. It also advises pairing with 'remember and recall', giving clear usage context and implicit guidance on 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.
ask_pipeworx and ask_pipeworx_beta are explicitly described as currently identical, creating real ambiguity between two tools. The polymarket cluster (arbitrage, edges, fill_risk, edge_tracker, kalshi_spread, bet_research) has overlapping edge-finding purposes that rely on reading long descriptions to separate, and the DNS tools are so few that an agent cannot tell this is a 'dns' server at all.
The set mixes at least four naming conventions: bare verbs (remember, forget, subscribe), verb_noun (dns_lookup, validate_claim, discover_tools), noun phrases (entity_profile, deep_research, recent_alerts), and brand-prefixed families (ask_pipeworx_*, polymarket_*, pipeworx_*). Each cluster is internally consistent, but the overall pattern is incoherent, including stray names like reverse_dns that invert the verb_first convention.
At 34 tools this exceeds the 25+ threshold for a heavy surface, and the count is wildly mismatched to the server's name: only 3 of 34 tools (dns_lookup, dns_lookup_all, reverse_dns) relate to DNS. The remaining 31 tools belong to unrelated domains (data research, prediction markets, memory, subscriptions, npm scanning), making the toolkit feel like a mislabeled grab-bag rather than a scoped server.
Judged against the server's stated 'dns' purpose, coverage is thin: read-only lookups only, with no WHOIS, DNSSEC, zone management, or write operations. Judged against the dominant inferred domain (a data-research/prediction-market platform), the surface is quite complete — query, grounded verification, deep research, profiles, comparisons, claim validation, discovery, subscriptions, alerts, and feedback all exist — though there is no tool to directly read a pipeworx:// citation URI.