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?
Description confirms destructive nature (delete) consistent with annotations (destructiveHint=true). No contradictions; does not add beyond annotations but aligns well.
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: first sentence states purpose, second provides usage guidelines. No wasted words, front-loaded.
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?
Simple tool with one parameter and annotations; description covers purpose, usage, and parameter. No output schema needed; complete for its complexity.
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?
Only one parameter 'key' with description 'Memory key to delete', which matches schema. Schema coverage 100%, so baseline 3 applies; no extra semantic detail added.
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?
Clearly states 'Delete a previously stored memory by key', using a specific verb and resource. Distinguishes from sibling tools like 'remember' and 'recall'.
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?
Explicitly provides three use cases (stale context, task done, clear sensitive data) and recommends pairing with remember and recall.
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.
The ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) is highly overlapping—two of them are explicitly identical right now—and the six polymarket_* tools plus bet_research create unclear boundaries between prediction-market analysis tools. Company-focused tools (entity_profile, compare_entities, recent_changes, resolve_entity) also partially overlap in what they fetch, making tool selection error-prone.
Most tool names follow a clear snake_case pattern with descriptive verbs (search_quotes, resolve_entity, validate_claim, subscribe, unsubscribe). There is good use of family prefixes like polymarket_* and pipeworx_*, though the Pipeworx family mixes prefix and suffix placement (ask_pipeworx vs. pipeworx_feedback), which is a minor inconsistency.
35 tools is far too many for a server named 'Quotable', especially since only 4 tools (get_authors, list_tags, random_quote, search_quotes) relate to quotes. The rest span data lookup, prediction markets, memory, subscriptions, AI visibility, and dependency scanning—an extremely broad, unfocused scope that overwhelms the apparent purpose.
The quote-related surface is minimal but functional (random, search, authors, tags), though missing obvious operations like get_quote_by_id. The data-lookup and prediction-market domains are thoroughly covered with grounding, research, arbitrage, and fill-risk tools, so the broader set is complete—but it does not serve the server's stated identity as a quotes provider.