metadataReturns MyVariant.info build metadata: total indexed variant count, available annotation sources (dbSNP, ClinVar, CADD, dbNSFP, gnomAD), and their current release/build versions.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {}
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, indicating safe, read-only behavior. The description adds context about what specific data is returned (total variants, sources, versions), which is valuable 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?
Single sentence that is well-structured and front-loaded with the key purpose. Every word contributes value, and there is no wasted text.
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 zero parameters, no output schema, and annotations covering safety, the description is complete. It lists the data returned, which is sufficient for an agent to understand and invoke the tool 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 input schema has zero parameters, so the description has no need to add parameter meaning. Baseline for 0 parameters is 4, and the description does not provide any param info, which 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 tool returns MyVariant.info build metadata, including specific data like variant count and annotation sources. This is a specific verb+resource combination that distinguishes it from sibling tools which are about querying or researching entities.
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 clear context for when to use the tool (to get metadata) but does not mention when not to use it or offer alternatives. Since there are no parameters and the tool is simple, the lack of explicit exclusion is acceptable but not optimal.
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 clusters have overlapping purposes: ask_pipeworx and ask_pipeworx_beta are explicitly identical, and the five prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_kalshi_spread, polymarket_fill_risk) all target 'find edge in Polymarket markets' with subtle differences. query and variant both retrieve the same variant annotations, and ai_visibility_check vs scan_competitor_ai_presence are near-duplicates.
Most tools follow a consistent verb_noun or domain-prefixed pattern (ask_pipeworx, compare_entities, resolve_entity, polymarket_edges, remember/recall/forget). Minor deviations exist: the bare nouns query, variant, and metadata are less descriptive, and ask_pipeworx_beta uses a suffix instead of a clean verb pattern, but the overall convention is fairly uniform.
34 tools is far too many for a server named 'Myvariant' whose stated domain is genetic variant annotations. The set is a grab-bag spanning genetic data, Pipeworx query routing, Polymarket betting, memory persistence, subscriptions, AI visibility, and npm dependency scanning. Most tools are unrelated to the server's apparent purpose, making the count feel bloated and incoherent.
Individual clusters are reasonably complete: variants have search/get/metadata, memory has remember/recall/forget, and subscriptions have subscribe/list/unsubscribe/alerts. However, as a Myvariant server the surface is massively over-scoped yet oddly missing any batch-variant or annotation-source-specific lookup, and the sprawling multi-domain design makes 'complete' hard to meaningfully assess.