fix(api): avoid stainless SDK NameError

Author: stainless-app[bot]

.stats.yml

@@ -1,4 +1,4 @@
 configured_endpoints: 4
-openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/isaacus%2Fisaacus-e92a3b3731be1b1223f26fce1a50165c75ea209097e89a530a6123a59c672898.yml
-openapi_spec_hash: ba79dfb28159963468d872e717579e94
+openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/isaacus%2Fisaacus-30c23c1facb9383eb94d78d16d6a45b7e6afd943caf94cddeb75fd86357294f7.yml
+openapi_spec_hash: 48a6b3192add4f538615ac6f190123c5
 config_hash: 886b5eef0dbd90b8e6686e987a07b816

packages/mcp-server/src/tools/embeddings/create-embeddings.ts

@@ -18,7 +18,7 @@ export const metadata: Metadata = {
 export const tool: Tool = {
   name: 'create_embeddings',
   description:
-    "When using this tool, always use the `jq_filter` parameter to reduce the response size and improve performance.\n\nOnly omit if you're sure you don't need the data.\n\nEmbed legal texts with an Isaacus legal AI embedder.\n\n# Response Schema\n```json\n{\n  $ref: '#/$defs/embedding',\n  $defs: {\n    embedding: {\n      type: 'object',\n      title: 'Embedding response',\n      description: 'Embeddings of legal texts produced by an Isaacus legal AI embedder.',\n      properties: {\n        embeddings: {\n          type: 'array',\n          description: 'The embeddings of the inputs.',\n          items: {\n            type: 'object',\n            title: 'Embedding',\n            properties: {\n              embedding: {\n                type: 'array',\n                description: 'The embedding of the content represented as an array of floating point numbers.',\n                items: {\n                  type: 'number'\n                }\n              },\n              index: {\n                type: 'integer',\n                description: 'The position of the content in the input array of contents, starting from `0` (and, therefore, ending at the number of contents minus `1`).'\n              }\n            },\n            required: [              'embedding',\n              'index'\n            ]\n          }\n        },\n        usage: {\n          type: 'object',\n          title: 'Embedding usage',\n          description: 'Statistics about the usage of resources in the process of embedding the inputs.',\n          properties: {\n            input_tokens: {\n              type: 'integer',\n              description: 'The number of tokens inputted to the model.'\n            }\n          },\n          required: [            'input_tokens'\n          ]\n        }\n      },\n      required: [        'embeddings',\n        'usage'\n      ]\n    }\n  }\n}\n```",
+    "When using this tool, always use the `jq_filter` parameter to reduce the response size and improve performance.\n\nOnly omit if you're sure you don't need the data.\n\nEmbed legal texts with an Isaacus legal AI embedder.\n\n# Response Schema\n```json\n{\n  $ref: '#/$defs/embedding',\n  $defs: {\n    embedding: {\n      type: 'object',\n      title: 'Embedding response',\n      description: 'Embeddings of legal texts produced by an Isaacus legal AI embedder.',\n      properties: {\n        embeddings: {\n          type: 'array',\n          description: 'The embeddings of the inputs.',\n          items: {\n            type: 'object',\n            title: 'Content embedding',\n            properties: {\n              embedding: {\n                type: 'array',\n                description: 'The embedding of the content represented as an array of floating point numbers.',\n                items: {\n                  type: 'number'\n                }\n              },\n              index: {\n                type: 'integer',\n                description: 'The position of the content in the input array of contents, starting from `0` (and, therefore, ending at the number of contents minus `1`).'\n              }\n            },\n            required: [              'embedding',\n              'index'\n            ]\n          }\n        },\n        usage: {\n          type: 'object',\n          title: 'Embedding usage',\n          description: 'Statistics about the usage of resources in the process of embedding the inputs.',\n          properties: {\n            input_tokens: {\n              type: 'integer',\n              description: 'The number of tokens inputted to the model.'\n            }\n          },\n          required: [            'input_tokens'\n          ]\n        }\n      },\n      required: [        'embeddings',\n        'usage'\n      ]\n    }\n  }\n}\n```",
   inputSchema: {
     type: 'object',
     properties: {