Cloudflare Workers MCP server: embedding-search
Maintain this server? Claim it
Call this server's tools from your browser. Nothing to install.
Requests go through mcptry because browsers can't call most MCP servers directly. Header values are sent to the server for that request only and are never stored or logged.
Tool list from our last check. Connect live to refresh it.
Compute cosine similarity between two texts. Returns score in [-1,1]. Useful for dedup and relatedness.
This tool isn't marked read-only, so it may change something on the server or in an account you connected.
Compute cosine similarity between two texts. Returns score in [-1,1]. Useful for dedup and relatedness.
| Argument | Type | Description |
|---|---|---|
| model | string | |
| text_a |
| string |
| text_b* | string |
{
"type": "object",
"required": [
"text_a",
"text_b"
],
"properties": {
"model": {
"type": "string"
},
"text_a": {
"type": "string"
},
"text_b": {
"type": "string"
}
}
}Generate vector embeddings for one or more texts using Cloudflare Workers AI (bge-base-en-v1.5, 768-dim).
| Argument | Type | Description |
|---|---|---|
| text* | any | Text or array of texts to embed |
| model | string | CF AI model ID override |
{
"type": "object",
"required": [
"text"
],
"properties": {
"text": {
"oneOf": [
{
"type": "string"
},
{
"type": "array",
"items": {
"type": "string"
}
}
],
"description": "Text or array of texts to embed"
},
"model": {
"type": "string",
"description": "CF AI model ID override"
}
}
}Rank a list of documents against a query using cosine similarity of bge embeddings. Returns top-k matches with scores.
| Argument | Type | Description |
|---|---|---|
| model | string | CF AI model ID override |
| query* | string | Search query |
| top_k | integer | Number of results (default 5) |
| documents* | array | Candidate documents to rank |
{
"type": "object",
"required": [
"query",
"documents"
],
"properties": {
"model": {
"type": "string",
"description": "CF AI model ID override"
},
"query": {
"type": "string",
"description": "Search query"
},
"top_k": {
"type": "integer",
"description": "Number of results (default 5)"
},
"documents": {
"type": "array",
"items": {
"type": "string"
},
"description": "Candidate documents to rank"
}
}
}