Skip to main content
Glama

Ensembl

by io.github.pipeworx-io

Vep

vep
Read-onlyIdempotent

"What's the effect of [variant]" / "predict consequences of [genomic change]" / "VEP for [chrom:pos]" — Variant Effect Predictor for a specified region + allele. Returns consequences (missense, synonymous, splice, etc.), affected genes, transcript impacts, SIFT/PolyPhen predictions. Use for variant interpretation in clinical or research genomics. THE REGION IS GRCh38 UNLESS YOU SET assembly. A GRCh37/hg19 position is still a valid GRCh38 position, so passing the wrong build returns confident annotations for a DIFFERENT locus rather than an error — check assembly_name in the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alleleYese.g. "C"
regionYese.g. "9:22125504-22125504:1" — in the build named by assembly (GRCh38 by default).
speciesYes
assemblyNoHuman genome build: "GRCh38" (the default) or "GRCh37" (= hg19). Coordinates you pass and coordinates you get back are both in this build. Older variant lists, spreadsheets and published tables are usually GRCh37.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of items returned.
itemsYesVariant Effect Predictor results

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "allele": "C",
-    "region": "9:22125504-22125504:1",
-    "species": "human"
-  }
-]New value: +[
+  {
+    "allele": "C",
+    "region": "9:22125504-22125504:1",
+    "species": "human"
+  },
+  {
+    "allele": "A",
+    "assembly": "GRCh37",
+    "region": "1:11856378-11856378:1",
+    "species": "human"
+  }
+]
    • addedInput schema / properties / assembly
      Added value: +{
+  "description": "Human genome build: \"GRCh38\" (the default) or \"GRCh37\" (= hg19). Coordinates you pass and coordinates you get back are both in this build. Older variant lists, spreadsheets and published tables are usually GRCh37.",
+  "type": "string"
+}
    • changedInput schema / properties / region / description
      Previous value: -"e.g. \"9:22125504-22125504:1\""New value: +"e.g. \"9:22125504-22125504:1\" — in the build named by assembly (GRCh38 by default)."
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "allele": "C",
+    "region": "9:22125504-22125504:1",
+    "species": "human"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of items returned.",
+      "type": "integer"
+    },
+    "items": {
+      "description": "Variant Effect Predictor results",
+      "items": {
+        "properties": {
+          "allele_string": {
+            "description": "Reference/alternate alleles",
+            "type": "string"
+          },
+          "end": {
+            "description": "End position",
+            "type": "integer"
+          },
+          "seq_region_name": {
+            "description": "Chromosome",
+            "type": "string"
+          },
+          "start": {
+            "description": "Start position",
+            "type": "integer"
+          },
+          "strand": {
+            "description": "Strand",
+            "type": "integer"
+          },
+          "transcript_consequences": {
+            "description": "Predicted consequences",
+            "items": {
+              "properties": {
+                "biotype": {
+                  "description": "Transcript biotype",
+                  "type": "string"
+                },
+                "consequence_terms": {
+                  "description": "Consequence term list",
+                  "items": {
+                    "type": "string"
+                  },
+                  "type": "array"
+                },
+                "gene_id": {
+                  "description": "Gene ID",
+                  "type": "string"
+                },
+                "hgvsc": {
+                  "description": "HGVS cDNA notation",
+                  "type": "string"
+                },
+                "hgvsp": {
+                  "description": "HGVS protein notation",
+                  "type": "string"
+                },
+                "impact": {
+                  "description": "Predicted impact",
+                  "type": "string"
+                },
+                "transcript_id": {
+                  "description": "Transcript ID",
+                  "type": "string"
+                }
+              },
+              "type": "object"
+            },
+            "type": "array"
+          },
+          "variant_id": {
+            "description": "Variant identifier",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "items",
+    "count"
+  ],
+  "type": "object"
+}
  3. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes beyond the annotations by warning that 'passing the wrong build returns confident annotations for a DIFFERENT locus rather than an error,' and advises checking assembly_name in the response. This alerts the user to a potential silent failure mode. The read-only, idempotent nature is already covered by annotations, so no conflict exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat wordy, starting with three repetitive phrasings before the core statement. The IMPORTANT warning in all caps adds emphasis but also makes the text longer. While the main purpose is clear, a more streamlined version would improve readability and focus.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives enough context for an agent to understand what the tool does, what inputs are needed, and what outputs to expect, including examples like missense and splice consequences. It also highlights a critical caveat about assembly builds, which is essential for correct usage. The lack of a formal output schema is offset by the descriptive list of result types.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides descriptions for three of four parameters (allele, region, assembly) with examples and build details, leaving species without a description. The tool description repeats the GRCh38 default but adds little beyond the schema, such as the note that coordinates are interpreted in the specified build. Overall, the parameter meanings are adequately conveyed, but the description does not significantly enhance the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'predict consequences of [genomic change]' and lists specific outputs like consequences, affected genes, and SIFT/PolyPhen predictions. It distinguishes itself from sibling tools by using the specific name 'Variant Effect Predictor' and emphasizing variant interpretation, making its role unique among available tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear use case: 'Use for variant interpretation in clinical or research genomics.' It also gives a practical caution about assembly build mismatches, which helps the user decide when to double-check coordinates. However, it does not explicitly mention alternatives or when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Ensembl toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation2/5

There is heavy overlap in the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research, validate_claim) — several are near-identical 'route a natural-language question to a source' tools differing only by small qualifiers. ai_visibility_check vs scan_competitor_ai_presence and entity_profile vs compare_entities vs recent_changes also blur together. An agent could easily misselect among these.

Naming Consistency4/5

The dominant convention is snake_case verb_noun/noun_verb (list_subscriptions, scan_dependency, validate_claim, resolve_entity) which is fairly consistent, but there are several bare single-word verbs (lookup, sequence, variation, vep, xrefs, recall, remember, forget) that break the pattern. No camelCase is present, so the inconsistency is minor rather than chaotic.

Tool Count2/5

38 tools is heavy, and the overwhelming majority (~31) are Pipeworx meta-tools (subscriptions, memory, feedback, trend, discovery, llms.txt generation) that have nothing to do with the server's declared Ensembl identity. Only about 7 tools are actually genomics-related, so the count is inflated by off-domain additions that dilute the surface.

Completeness2/5

For the Ensembl domain, the surface covers gene lookup, symbol resolution, sequence retrieval, orthologs, SNPs, variant effect prediction, and xrefs — but misses major Ensembl capabilities like gene trees/families, regulatory features, comparative/multi-species alignments, expression data, phenotypes, GO/ontology annotations, and region/overlap queries. Conversely the Pipeworx tools are complete for their own domain but irrelevant here, leaving the declared domain notably incomplete.

Resources