@voxell/forge-mcp

An MCP server for Forge — Voxell's hosted text-embedding API. It exposes Forge to any MCP client (Claude, Cursor, Cline, Windsurf, VS Code, …) as two tools:

• embed — turn text into vectors
• list_models — list available models and their dimensions

You bring a Forge API key. The server is stateless, and Voxell does not store the text you send or the vectors it returns — only usage metadata (token counts) is recorded, for billing. It does embeddings only — no storage, no search, no RAG. Those are different products.

Why Forge

• Quality you can dial. Forge runs the Qwen3-Embedding family; ultra is the 8B — ~75+ average task score on MTEB, currently #4 on MTEB (English), and the top usable model (the three ranked above it are research-only). turbo (0.6B) is the fast/cheap default. Pick your quality/cost point.
• Matryoshka (MRL). Set dim to truncate (re-normalized) for ~4× smaller, cheaper vectors.
• Low latency (Go + CUDA engine), zero-trust (per-key auth; mTLS available), and free to start (10M tokens, no card — dash.voxell.ai; more at voxell.ai/forge).

What you can do with it

• Add semantic search — embed your documents with input_type: "document" and each query with input_type: "query", then rank by cosine similarity.
• Build RAG — embed a knowledge base, store the vectors, and retrieve the closest chunks to ground an LLM.
• Find similar or duplicate text — embed two texts and compare their vectors.
• Cluster or classify — embed a batch, then cluster or train a classifier on the vectors.
• Shrink vector storage — set dim to truncate (Matryoshka) and trade a little accuracy for smaller, cheaper vectors.
• Straight from your editor — ask your AI agent (Cursor, Claude, …) to embed a snippet, a batch, or a file via the embed tool — no separate script.

Requirements

• Node.js ≥ 18 (tested on 20)
• A Forge API key — create one at https://dash.voxell.ai. New accounts start with 10M free tokens, no credit card.

Use it

Most MCP clients run it on demand with npx. Add this to your client's MCP config:

{
  "mcpServers": {
    "forge": {
      "command": "npx",
      "args": ["-y", "@voxell/forge-mcp"],
      "env": { "FORGE_API_KEY": "your-key-here" }
    }
  }
}

(Cursor, Claude Desktop, Cline, Windsurf, and VS Code all use this mcpServers shape.)

Tools

embed

| arg | type | default | notes | |-----|------|---------|-------| | input | string or string[] | — | text(s) to embed (required) | | model | string | turbo | turbo (1024-d), pro (2560-d), ultra (4096-d) | | dim | number | model default | truncate to N dimensions (Matryoshka) — works on every model | | input_type | "query" | "document" | document | use query for search queries |

Returns the vectors plus the model, dimension, and token count.

Default is turbo — the one you probably want. pro/ultra trade size and speed for more dimensions.

list_models

Lists the available models and their dimensions.

Configuration

| env | required | default | |-----|----------|---------| | FORGE_API_KEY | yes | — | | FORGE_BASE_URL | no | https://api.voxell.ai |

License

MIT © Voxell, Inc.