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 description's 'Delete' is consistent and adds minimal extra behavioral context. It does add a note about 'sensitive data,' slightly enriching the safety profile, but doesn't go beyond what annotations convey overall.
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 only two sentences, front-loads the main action, and every phrase adds value—purpose, usage guidance, and sibling relationships—without any fluff.
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?
With only one parameter, complete schema coverage, and appropriate annotations, this simple tool is well-covered. The description explains when and why to use it and even identifies related tools, making it sufficiently complete for an agent to invoke correctly.
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 description coverage is 100%, and the 'key' parameter is fully documented as 'Memory key to delete.' The description adds no extra parameter-level detail, so the 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 verb and resource: 'Delete a previously stored memory by key.' It also distinguishes itself from siblings by explicitly pairing with 'remember and recall,' making it evident that it is the inverse of remember.
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 provides explicit contexts for use: 'when context is stale, the task is done, or you want to clear sensitive data.' It mentions complementary tools (remember and recall) but does not explicitly state when not to use it, which keeps it at a 4 rather than a 5.
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.
Multiple tool families heavily overlap: ask_pipeworx, ask_pipeworx_beta (explicitly identical), ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language questions, while polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread, and bet_research all analyze prediction markets. An agent would struggle to pick the correct tool without reading very long descriptions.
All names are snake_case and readable, but the style is inconsistent: some are bare nouns (sequence, variation, homology), some are single verbs (lookup, recall, forget), and others are long descriptive phrases (scan_competitor_ai_presence, polymarket_kalshi_spread). There is no consistent verb_noun or resource_noun pattern across the set.
38 tools is excessive for a coherent server, and nearly all of them are unrelated to the server's stated name ('Ensembl') — only about 7 tools (lookup, lookup_symbol, sequence, variation, vep, xrefs, homology) actually belong to the Ensembl domain. The rest form several unrelated clusters (Pipeworx data queries, prediction markets, memory, subscriptions), making the tool count feel bloated and unfocused.
For an Ensembl server, the surface is thin: it covers ID lookup, sequence retrieval, variants, VEP, xrefs, and homology, but omits other core Ensembl functionality such as gene trees, alignments, regulation, expression, and assembly data. Meanwhile the many non-Ensembl tools don't form a complete domain of their own — they are a grab bag of unrelated utilities.