veryfront__upsert_file_chunk_embeddingsAccess
No external-service connection is required. Use a Veryfront credential with access to the requested resources. Call type: Can change resources.Arguments
| Field | Type | Required | Description and constraints |
|---|---|---|---|
project_reference | string | No | Project identifier or slug that scopes the tool call. |
chunk_ids | string[] | Yes | Chunk IDs to upsert embeddings for. |
vectors | number[][] | Yes | Embedding vectors aligned by index with chunk_ids. |
model | object | Yes | Embedding model that produced these vectors. Not an agent chat model; model listings omit it. |
Example request
Send this JSON-RPC request through an initialized MCP client. Replace sample identifiers and values before calling the tool. See MCP client setup.request.json
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "veryfront__upsert_file_chunk_embeddings",
"arguments": {
"chunk_ids": [],
"vectors": [],
"model": {
"name": "example",
"provider": "example",
"dimension": 0
}
}
}
}
Result
The published output shape is summarized below. Inspect both the MCP response content andisError when handling a call.
| Field | Type | Required | Description and constraints |
|---|---|---|---|
embeddings | object[] | Yes | Embeddings that were created or updated. |
created | number | Yes | Number of embeddings created. |
updated | number | Yes | Number of embeddings updated. |
Full schemas
{
"type": "object",
"properties": {
"project_reference": {
"type": "string",
"description": "Project identifier or slug that scopes the tool call."
},
"chunk_ids": {
"type": "array",
"items": {
"type": "string",
"format": "uuid",
"description": "One chunk id item supplied to the tool."
},
"maxItems": 100,
"description": "Chunk IDs to upsert embeddings for."
},
"vectors": {
"type": "array",
"items": {
"type": "array",
"items": {
"type": "number",
"description": "One item item supplied to the tool."
},
"maxItems": 4096,
"description": "One vector item supplied to the tool."
},
"maxItems": 100,
"description": "Embedding vectors aligned by index with `chunk_ids`."
},
"model": {
"type": "object",
"properties": {
"name": {
"type": "string",
"minLength": 1,
"description": "Model name, for example `text-embedding-3-small`."
},
"provider": {
"type": "string",
"minLength": 1,
"description": "Provider name, for example `openai`."
},
"dimension": {
"type": "number",
"description": "Embedding vector dimension: 768, 1024, 1536, 3072, or 4096. Every vector must have this length."
}
},
"required": [
"name",
"provider",
"dimension"
],
"additionalProperties": false,
"description": "Embedding model that produced these vectors. Not an agent chat model; model listings omit it."
}
},
"required": [
"chunk_ids",
"vectors",
"model"
],
"additionalProperties": false,
"description": "Arguments for the upsert_file_chunk_embeddings tool.",
"$schema": "http://json-schema.org/draft-07/schema#"
}
{
"type": "object",
"properties": {
"embeddings": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Embedding ID."
},
"model": {
"type": "string",
"description": "Embedding model name used to create the vector."
},
"status": {
"type": "string",
"enum": [
"ready",
"stale",
"missing"
],
"description": "Embedding lifecycle status."
},
"created_at": {
"type": "string",
"description": "Embedding creation timestamp in ISO 8601 format."
}
},
"required": [
"id",
"model",
"status",
"created_at"
],
"additionalProperties": false
},
"description": "Embeddings that were created or updated."
},
"created": {
"type": "number",
"description": "Number of embeddings created."
},
"updated": {
"type": "number",
"description": "Number of embeddings updated."
}
},
"required": [
"embeddings",
"created",
"updated"
],
"additionalProperties": false,
"description": "Structured result returned by the upsert_file_chunk_embeddings tool.",
"$schema": "http://json-schema.org/draft-07/schema#"
}