Opentargets

Target Associations

target_associations

Read-onlyIdempotent

"What diseases is [gene] involved in" / "diseases associated with [target]" / "what does [gene] cause" — top disease associations for a drug target (Ensembl gene ID), scored by integrated Open Targets evidence (genetics, expression, animal models, drugs, literature, pathways). Use to triage what diseases a candidate target might address.

Input Schema

Name	Required	Description	Default
`size`	No	1-50 (default 10)
`ensembl_id`	Yes

Output Schema

Name	Required	Description	Default
`target`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 11, 2026

removedOutput schema / properties / data

Removed value: -{
-  "properties": {
-    "target": {
-      "properties": {
-        "approvedSymbol": {
-          "description": "Target symbol",
-          "type": "string"
-        },
-        "associatedDiseases": {
-          "properties": {
-            "count": {
-              "description": "Total disease associations",
-              "type": "integer"
-            },
-            "rows": {
-              "items": {
-                "properties": {
-                  "disease": {
-                    "properties": {
-                      "id": {
-                        "description": "Disease ID",
-                        "type": "string"
-                      },
-                      "name": {
-                        "description": "Disease name",
-                        "type": "string"
-                      }
-                    },
-                    "type": "object"
-                  },
-                  "score": {
-                    "description": "Association score",
-                    "type": "number"
-                  }
-                },
-                "type": "object"
-              },
-              "type": "array"
-            }
-          },
-          "type": "object"
-        },
-        "id": {
-          "description": "Target ID",
-          "type": "string"
-        }
-      },
-      "type": "object"
-    }
-  },
-  "type": "object"
-}

addedOutput schema / properties / target

Added value: +{
+  "properties": {
+    "approvedSymbol": {
+      "type": "string"
+    },
+    "associatedDiseases": {
+      "properties": {
+        "count": {
+          "type": "number"
+        },
+        "rows": {
+          "items": {
+            "properties": {
+              "disease": {
+                "properties": {
+                  "id": {
+                    "type": "string"
+                  },
+                  "name": {
+                    "type": "string"
+                  }
+                },
+                "type": "object"
+              },
+              "score": {
+                "type": "number"
+              }
+            },
+            "type": "object"
+          },
+          "type": "array"
+        }
+      },
+      "type": "object"
+    },
+    "id": {
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

Changed2 schema fields changedMay 22, 2026

addedInput schema / examples

Added value: +[
+  {
+    "ensembl_id": "ENSG00000141510"
+  },
+  {
+    "ensembl_id": "ENSG00000141510",
+    "size": 25
+  }
+]

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "data": {
+      "properties": {
+        "target": {
+          "properties": {
+            "approvedSymbol": {
+              "description": "Target symbol",
+              "type": "string"
+            },
+            "associatedDiseases": {
+              "properties": {
+                "count": {
+                  "description": "Total disease associations",
+                  "type": "integer"
+                },
+                "rows": {
+                  "items": {
+                    "properties": {
+                      "disease": {
+                        "properties": {
+                          "id": {
+                            "description": "Disease ID",
+                            "type": "string"
+                          },
+                          "name": {
+                            "description": "Disease name",
+                            "type": "string"
+                          }
+                        },
+                        "type": "object"
+                      },
+                      "score": {
+                        "description": "Association score",
+                        "type": "number"
+                      }
+                    },
+                    "type": "object"
+                  },
+                  "type": "array"
+                }
+              },
+              "type": "object"
+            },
+            "id": {
+              "description": "Target ID",
+              "type": "string"
+            }
+          },
+          "type": "object"
+        }
+      },
+      "type": "object"
+    }
+  },
+  "type": "object"
+}

First observedMay 14, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuine behavioral context beyond that by disclosing the scoring basis (integrated Open Targets evidence across genetics, expression, animal models, drugs, literature, pathways), which tells the agent how results are ranked. It omits limits, pagination, and coverage caveats, so not a 5.

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

Conciseness4/5

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

Single dense sentence with the user-intent examples front-loaded and the scoring detail trailing. Nothing is wasted, though the parenthetical evidence list is long enough to slightly dilute the front-loading.

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?

With an output schema present, return values need not be explained, and the description covers purpose, scoring methodology, and use case. The remaining gap is disambiguation from the inverse/related siblings (disease_associations, target_known_drugs), which an agent choosing among these tools would benefit from.

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?

Schema description coverage is 50%: size documents its range and default, but ensembl_id has no schema description. The description partially compensates by identifying the identifier as an Ensembl gene ID, which is the key semantic an agent needs. It adds nothing further, so the baseline 3 for a schema that does most of the heavy lifting is appropriate.

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

Purpose4/5

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

States a specific resource (top disease associations) and the exact input identifier (Ensembl gene ID), with the natural-language query examples making the intent instantly matchable. It implicitly separates from siblings like target_known_drugs and disease_associations by naming the resource as 'disease associations for a drug target,' but it never names an alternative tool explicitly, so it falls short of a 5.

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?

"Use to triage what diseases a candidate target might address" gives a clear, concrete context of use. There is no explicit when-not guidance and no named alternative (e.g., disease_associations or target_known_drugs), so it stops at clear context without exclusions.

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

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