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Forge MCP Server

@VoxellInc

代码仓库

基本信息

分类

记忆与知识

传输方式

stdio

作者

VoxellInc

提交者

Jonathan Corners

关于 Forge MCP Server

Forge is Voxell's hosted text-embedding API. This MCP server exposes two tools — embed (turn text into vectors) and list_models — so any MCP-compatible agent can generate embeddings for semantic search, RAG, clustering, and dedup.

#embeddings#text-embedding#vector#semantic-search#rag#retrieval#vector-search#voxell#forge#qwen3#matryoshka#embedding-api#nlp#similarity

Forge MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Forge MCP Server 工具

2

Generate vector embeddings for one or more texts with Forge (Voxell's hosted embedding API). Use it to turn text into vectors for semantic search, RAG, clustering, or similarity. Set input_type='query' for search queries and 'document' for content you index. Choose model by quality/cost: turbo (1024d, fast, default) -> pro (2560d) -> ultra (4096d, #4 on MTEB English, top usable). Optionally set dim to truncate (Matryoshka, re-normalized).

List the available Forge embedding models and their dimensions. Call this to pick a model before embedding.

概览

What is Forge?

Forge is an MCP (Model Context Protocol) server for Voxell's hosted text-embedding API. It exposes two tools (embed and list_models) to any MCP client, including Claude, Cursor, Cline, Windsurf, and VS Code. The server is stateless; Voxell does not store the text sent or the vectors returned — only usage metadata (token counts) for billing.

How to use Forge?

Install via one-click links for Cursor or VS Code, or with a CLI command for Claude Code. Configure your MCP client with a mcpServers block that runs npx -y @voxell/forge-mcp and sets the FORGE_API_KEY environment variable. Requires Node.js ≥ 18 and a Forge API key from https://dash.voxell.ai.

Key features of Forge

  • Provides embed (text to vectors) and list_models tools.
  • Supports Matryoshka (MRL) dimension truncation for smaller vectors.
  • Runs the Qwen3-Embedding model family (turbo, pro, ultra).
  • Low latency (Go + CUDA engine), zero-trust, per-key auth.
  • No storage of text or vectors – only usage metadata recorded.
  • Also offers an OpenAI-compatible API for seamless migration.

Use cases of Forge

  • Add semantic search by embedding documents and queries separately.
  • Build RAG pipelines by embedding a knowledge base and retrieving relevant chunks.
  • Find similar or duplicate text by comparing vector embeddings.
  • Cluster or classify text by embedding batches then applying ML algorithms.
  • Shrink vector storage by truncating dimensions via Matryoshka.

常见问题

1

What does Forge do vs other MCP servers?

Forge is strictly an embedding server – it does not provide storage, search, or RAG. Those are separate products.

2

What are the runtime requirements?

Node.js version 18 or higher (tested on 20) and a valid Forge API key. New accounts start with 10M free tokens, no credit card required.

3

Where does my data go?

The server is stateless. Voxell does not store the text you send or the vectors it returns. Only usage metadata (token counts) is recorded for billing.

4

What authentication does Forge use?

Authentication is via an API key set in the `FORGE_API_KEY` environment variable. mTLS is available for extra security.

5

What transport does Forge use?

Forge runs as a standard MCP server, launched via `npx`. It connects over standard I/O (stdio) to the MCP client.

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