puspoaditya/cloudflare-workers-ai-mcp

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
| Tool | Description |
|---|---|
| list_models | List supported chat, embedding, and image models |
| chat_completion | LLM chat completion (Llama 3.3 70B, Llama 3.1 8B, Llama 4 Scout, Qwen Coder 32B, DeepSeek R1 Distill) |
| embed_text | Text embeddings (BGE small/base) |
| generate_image | Image 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:
Run
Claude Desktop
Add to claude_desktop_config.json:
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.