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 indicate destructiveHint=true and idempotentHint=true. Description adds 'Delete' but doesn't clarify behavior for non-existent keys or side effects. With annotations, minimal extra info provided.
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, concise and front-loaded with purpose. No unnecessary 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 good annotations, the description is largely complete. Could mention permanence of deletion but not critical.
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 covers 100% of parameters with description 'Memory key to delete'. Description doesn't add beyond schema, so baseline 3.
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.' The verb 'Delete' and resource 'memory by key' are specific, distinguishing it from siblings 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 states when to use: 'when context is stale, the task is done, or you want to clear sensitive data' and mentions pairing with remember and recall for context.
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.
Each tool has a clearly distinct purpose. Even closely related tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research are well-differentiated by their use cases and safety guarantees. The multiple polymarket tools each focus on a unique aspect (arbitrage, edge scanning, persistence, fill risk, cross-venue spreads), avoiding ambiguity.
All tool names use lowercase with underscores, following a mostly verb_noun or domain_prefix_noun pattern (e.g., ask_pipeworx, entity_profile, resolve_entity). A few names like dataset_info and ai_visibility_check deviate slightly from a strict verb_noun structure, but the overall pattern is predictable and readable.
With 33 tools, the server is on the heavier end of the well-scoped range. However, the count is justified by the breadth of functionality: data queries, prediction markets, entity resolution, memory, monitoring, and more. The tools each serve a specific purpose, and none feel redundant.
The tool surface covers a wide range of use cases including data retrieval, comparison, research, monitoring, and memory. Minor gaps exist (e.g., no tool for placing prediction market trades or creating/updating Tours Métropole datasets), but these are likely intentional scope choices. Core workflows are well-supported.