# Fast Embedding MCP SSE

> Use this tool when you need to efficiently embed and compare text data, or perform similarity searches, to solve problems like text classification, clustering, or information retrieval. It takes in text inputs and outputs embedded vectors, similarity scores, or search results via an OpenAI-compatible HTTP API. Ideal for applications requiring fast and scalable natural language processing capabilities.

Canonical page: https://skillsregistry.net/skills/rikka-botan-fast-embedding-mcp-sse  
JSON: https://api.skillsregistry.net/v1/skills/rikka-botan-fast-embedding-mcp-sse

## Description

Provides fast static embedding, similarity, and search capabilities via MCP tools and an OpenAI-compatible HTTP API using a tiny 16M-parameter English embedding model.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/e3lxevwq7q)
- **Repository:** <https://github.com/Rikka-Botan/Fast-Embedding-MCP-SSE>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "rikka-botan-fast-embedding-mcp-sse"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rikka-botan-fast-embedding-mcp-sse` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rikka-botan-fast-embedding-mcp-sse/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt