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. Description confirms destructive action ('Delete') but adds no extra context beyond 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?
Two sentences covering purpose, usage guidelines, and sibling references. Every sentence adds value; front-loaded with main action.
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 required parameter and no output schema. Description fully covers purpose, usage context, and destructive nature, supported by annotations.
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?
Single parameter 'key' is fully described in schema; description adds no additional meaning beyond what schema provides.
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?
Description clearly states action (Delete) and resource (previously stored memory by key). Also distinguishes from siblings by referencing '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 states when to use: when context is stale, task done, or clearing sensitive data. Mentions pairing with related tools, but no explicit when-not scenarios.
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 tool clusters have unclear boundaries: ask_pipeworx, ask_pipeworx_beta (explicitly identical), ask_pipeworx_grounded, and deep_research all route the same queries, and the five polymarket_* tools overlap in opportunity scanning. entity_profile, compare_entities, and recent_changes also pull similar company data, making tool selection genuinely ambiguous.
All tool names are snake_case with a mostly verb-first convention (ask_pipeworx, scan_dependency, validate_claim, resolve_entity). A few noun-first names like polymarket_edges, entity_profile, and recent_alerts deviate slightly, but the pattern is predictable and readable throughout the 34-tool set.
At 34 tools, the surface is heavy for what the server name (Data Cincinnati) implies, and only 3 tools actually relate to Cincinnati open data. The rest spans prediction markets, npm analysis, AI visibility, memory, and subscriptions, suggesting either scope creep or a misleading server name.
The research workflow is fairly covered: discovery (discover_tools, suggest_questions), query (ask_pipeworx), grounding (ask_pipeworx_grounded), verification (validate_claim), profiling (entity_profile), comparison (compare_entities), and monitoring (subscribe, recent_changes). However, notable gaps exist — no direct single-source raw query, no export/visualization, no subscription or alert management details beyond basic CRUD, and the Cincinnati-specific surface is thin (no geospatial or full-catalog access).