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, so the description's mention of 'delete' aligns. The description adds context about clearing sensitive data but does not reveal additional behavioral details beyond the 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 concise with two sentences, no wasted words. It is front-loaded with the core action and provides usage guidance efficiently.
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 the tool's simplicity (one parameter, no output schema), the description is complete: it explains the action, when to use, and how it relates to sibling tools. No gaps remain.
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 coverage is 100% with a clear description for the 'key' parameter ('Memory key to delete'). The description does not add extra meaning beyond what the schema provides, so a 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 clearly states the action ('Delete') and the resource ('previously stored memory by key'). It also distinguishes itself from siblings by mentioning pairing with '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?
The description explicitly states when to use the tool: when context is stale, task is done, or to clear sensitive data. It also references sibling tools ('Pair with remember and recall'), providing clear usage guidance.
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 route to the same underlying Pipeworx engine (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research), and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. The polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) and the entity-investigation tools (entity_profile, compare_entities, recent_changes, resolve_entity) also have heavily overlapping purposes that an agent could easily confuse.
Most tools use snake_case, but the set mixes verb-first names (get_specimen, search_specimens, resolve_entity, validate_claim) with noun-first names (entity_profile, recent_alerts, polymarket_edges, pipeworx_trending). The polymarket_ and pipeworx_ prefixes give some internal consistency, but the overall pattern is not uniform.
34 tools is heavy for a server named Idigbio, especially since only 3 of the 34 tools (count_by_field, get_specimen, search_specimens) actually relate to iDigBio specimen data. The remaining 31 are a sprawling Pipeworx/prediction-market/marketing/memory toolkit, making the tool count mismatched with the server's apparent identity.
The Pipeworx side is quite complete: querying, grounded answers, deep research, entity profiles, comparisons, claim validation, subscriptions, memory, and feedback are all present. However, the iDigBio side, which the server name advertises, is only minimally covered with search/get/count and lacks any collection or media download operations, so the overall surface has notable gaps relative to the server's stated focus.