geneGene info + variants. Accepts gene symbol (e.g. "BRCA1") or Ensembl gene id.
| Name | Required | Description | Default |
|---|---|---|---|
| dataset | No | ||
| gene_symbol_or_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| gene | No | ||
| gene_search | No | Gene search results |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "gene_symbol_or_id": "BRCA1"
+ },
+ {
+ "dataset": "gnomad_r4",
+ "gene_symbol_or_id": "ENSG00000139618"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "gene": {
+ "properties": {
+ "chrom": {
+ "description": "Chromosome",
+ "type": "string"
+ },
+ "gene_id": {
+ "description": "Ensembl gene ID",
+ "type": "string"
+ },
+ "name": {
+ "description": "Full gene name",
+ "type": "string"
+ },
+ "start": {
+ "description": "Gene start position",
+ "type": "number"
+ },
+ "stop": {
+ "description": "Gene stop position",
+ "type": "number"
+ },
+ "strand": {
+ "description": "Strand orientation",
+ "type": "string"
+ },
+ "symbol": {
+ "description": "Gene symbol",
+ "type": "string"
+ },
+ "variants": {
+ "items": {
+ "properties": {
+ "consequence": {
+ "description": "VEP consequence",
+ "type": "string"
+ },
+ "exome": {
+ "properties": {
+ "ac": {
+ "description": "Allele count",
+ "type": "number"
+ },
+ "af": {
+ "description": "Allele frequency",
+ "type": "number"
+ },
+ "an": {
+ "description": "Allele number",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "genome": {
+ "properties": {
+ "ac": {
+ "description": "Allele count",
+ "type": "number"
+ },
+ "af": {
+ "description": "Allele frequency",
+ "type": "number"
+ },
+ "an": {
+ "description": "Allele number",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "hgvsc": {
+ "description": "HGVS cDNA notation",
+ "type": "string"
+ },
+ "hgvsp": {
+ "description": "HGVS protein notation",
+ "type": "string"
+ },
+ "rsids": {
+ "description": "rsID identifiers",
+ "type": [
+ "array",
+ "null"
+ ]
+ },
+ "variant_id": {
+ "description": "Variant identifier",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+ },
+ "gene_search": {
+ "description": "Gene search results",
+ "items": {
+ "properties": {
+ "ensembl_id": {
+ "description": "Ensembl gene ID",
+ "type": "string"
+ },
+ "symbol": {
+ "description": "Gene symbol",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, open-world, and non-destructive behavior. The description adds that the tool accepts two identifier formats, a mild behavioral trait, but does not disclose error handling or data scoping beyond that.
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 a single sentence, front-loaded with the core function. Every word earns its place with no filler.
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 read-only lookup with an output schema and clear annotations, the description is minimally adequate. However, the vague 'gene info + variants' and the undocumented dataset parameter leave some gaps in fully understanding the tool's capabilities.
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 description explains that gene_symbol_or_id accepts a gene symbol or Ensembl ID, which adds meaning to that parameter. However, the dataset parameter is not explained, and with 0% schema description coverage, this leaves a gap for agents.
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 provides gene information and variants, and specifies accepted identifier types (gene symbol or Ensembl gene ID). This distinguishes it from related tools like variant and region, though the meaning of 'info' is slightly vague.
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?
It gives context on what inputs are acceptable (gene symbol or Ensembl gene ID), which implies when to use the tool, but it does not explicitly mention alternatives or exclusions, such as when to use the variant tool instead.
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.
The set mixes several overlapping query surfaces: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded/deep_research/discover_tools/suggest_questions all serve related retrieval/discovery purposes, and the five polymarket_* tools have similar opportunity-finding goals. Only the unusually detailed descriptions save some tools from misselection; an agent would struggle to quickly pick the right one.
Names are uniformly snake_case and mostly follow a verb_noun or prefixed_noun pattern (ask_pipeworx, validate_claim, polymarket_edges, scan_dependency). Minor inconsistencies exist — bare nouns like gene/variant/search sit alongside compound names like generate_llms_txt, and the pipeworx_ prefix isn't applied to ask_pipeworx/deep_research — but the overall style is recognizable and predictable.
36 tools is too many for a coherent server, especially since the domains are largely unrelated: 5 gnomAD genomics tools, 20+ Pipeworx/Polymarket data tools, memory CRUD, subscription management, and a couple of web-dev utilities. The count doesn't align with a single obvious scope and would overwhelm an agent selecting among them.
Within the major subdomains coverage is strong: memory has remember/recall/forget, subscriptions have full lifecycle tools, and Polymarket has edge detection plus fill-risk checking. However, there are notable gaps — no tool to fetch a pipeworx:// citation URI despite deep_research promising resolvable citations, and the gnomAD surface lacks batch queries, coverage, or constraint data for a server named Gnomad.