Cloudflare Workers AI MCP

Communauté Cloud et DevOps

Cloudflare Workers AI inference: LLM chat completions (Llama, Qwen, DeepSeek), BGE text embeddings and Flux image generation.

Installation

Les étapes d'installation sont dans la documentation ci-dessous. Documentation

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Cloudflare Workers AI MCP Server
  2. Tools
  3. Setup
  4. Run
  5. Example prompts
  6. Models (verified live)
  7. Test
  8. License

Cloudflare Workers AI MCP Server

Model Context Protocol (MCP) server that gives AI agents access to Cloudflare Workers AI — serverless LLM inference, embeddings, and image generation with a generous free tier.

Tools

ToolDescription
list_modelsList supported chat, embedding, and image models
chat_completionLLM chat completion (Llama 3.3 70B, Llama 3.1 8B, Llama 4 Scout, Qwen Coder 32B, DeepSeek R1 Distill)
embed_textText embeddings (BGE small/base)
generate_imageImage generation (Flux 1 Schnell) → base64 image (PNG/JPEG)

Setup

  1. Create a Cloudflare API token with the Workers AI permission: https://dash.cloudflare.com/profile/api-tokens
  2. Get your Account ID (right sidebar of the Cloudflare dashboard, or the /accounts/{id} segment of any dashboard URL)
  3. Export the env vars:
export CLOUDFLARE_ACCOUNT_ID="your-account-id"
export CLOUDFLARE_API_TOKEN="your-api-token"

Run

npm install && npm run build
npm start   # stdio MCP server
Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "cloudflare-workers-ai": {
      "command": "node",
      "args": ["/absolute/path/to/cloudflare-workers-ai-mcp/dist/index.js"],
      "env": {
        "CLOUDFLARE_ACCOUNT_ID": "your-account-id",
        "CLOUDFLARE_API_TOKEN": "your-api-token"
      }
    }
  }
}
Cursor / VS Code / other MCP clients

Point the client at the same command (node dist/index.js with the two env vars).

OpenClaw

OpenClaw supports MCP servers — add the same command to its MCP configuration.

Example prompts

  • "Summarize this text using the Llama 3.3 70B model on Cloudflare Workers AI"
  • "Generate an image of a red fox in a snowstorm"
  • "Embed these 3 sentences for a similarity search"

Models (verified live)

Chat: POST /ai/v1/chat/completions (OpenAI-compatible) · Embeddings & images: POST /ai/run/{model} (native)

Models — chat: @cf/meta/llama-3.3-70b-instruct-fp8-fast · @cf/meta/infire-llama-3.1-8b-instruct · @cf/meta/llama-4-scout-17b-16e-instruct · @cf/qwen/qwen2.5-coder-32b-instruct · @cf/deepseek-ai/deepseek-r1-distill-qwen-32b

Embeddings: @cf/baai/bge-small-en-v1.5 · @cf/baai/bge-base-en-v1.5

Images: @cf/black-forest-labs/flux-1-schnell

Note: @cf/meta/llama-3.1-8b-instruct was deprecated by Cloudflare (2026-05-30) — use @cf/meta/infire-llama-3.1-8b-instruct.

Test

npm test   # unit tests (mocked fetch) + protocol test

License

MIT — built by puspoaditya.

Questions fréquentes

Qu'est-ce que Cloudflare Workers AI MCP ?

Cloudflare Workers AI inference: LLM chat completions (Llama, Qwen, DeepSeek), BGE text embeddings and Flux image generation.

Comment installer Cloudflare Workers AI MCP ?

Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.

Cloudflare Workers AI MCP est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Cloudflare Workers AI MCP ?

Il est publié par puspoaditya. AI.tn le référence sans le maintenir ni le recommander.

Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.