NanoBananaPro

<h1>genai-mcp: GenAI MCP Server for Image Generation(eg. Nano Banana)</h1>

GenAI MCP Server

This project implements a Model Context Protocol (MCP) server for image generation and image editing using Google Gemini (via google.golang.org/genai) and Tongyi Wanxiang (Ali Bailian) image APIs, plus optional automatic upload of generated images to S3‑compatible object storage (AWS S3, Aliyun OSS, etc.).

The server exposes a streamable HTTP MCP endpoint and provides tools for Gemini and Wan:

• gemini_generate_image – text → image
• gemini_edit_image – image + text → edited image

Gemini / Nano Banana backend support

This MCP server currently supports the following Gemini‑compatible backends:

1. Google official Gemini API

   • Use the default GENAI_BASE_URL=https://generativelanguage.googleapis.com
   • GENAI_API_KEY is a Google Gemini API key

2. dmxapi (Gemini‑compatible third‑party gateway)

   • Set GENAI_BASE_URL to the dmxapi Gemini endpoint (for example https://www.dmxapi.cn)
   • GENAI_API_KEY is the key issued by dmxapi
   • As long as the endpoint implements the google.golang.org/genai compatible Gemini API, no code changes are needed

Tongyi Wanxiang (Ali Bailian) backend support

When GENAI_PROVIDER=wan, the server will use Ali Bailian Tongyi Wanxiang image APIs (via DashScope) instead of Gemini:

• Set:
  • GENAI_PROVIDER=wan
  • GENAI_BASE_URL=https://dashscope.aliyuncs.com
  • GENAI_API_KEY=<your DashScope API key>
  • GENAI_GEN_MODEL_NAME=wan2.5-t2i-preview (text → image)
  • GENAI_EDIT_MODEL_NAME=wan2.5-i2i-preview (image → image)
• Wan provides a separate MCP tool set (see internal/tools/wan.go):
  • wan_create_generate_image_task
  • wan_query_generate_image_task
  • wan_create_edit_image_task
  • wan_query_edit_image_task

The Python test client in tests/mcp_client.py will automatically route calls to Gemini or Wan based on GENAI_PROVIDER (gemini by default, wan for Tongyi Wanxiang).

---

1. Prerequisites

• Go 1.21+ (recommended; go.mod uses module mode)
• A valid Gemini API key
• Optional: S3 / OSS bucket for storing images

---

2. Configuration (.env)

Copy env.example to .env, then fill in real values.

GenAI configuration

# GenAI provider:
# - gemini: Google Gemini / compatible backend
# - wan:    Ali Bailian Tongyi Wanxiang image APIs
GENAI_PROVIDER=gemini

# Shared GenAI endpoint / key for both providers
GENAI_BASE_URL=https://generativelanguage.googleapis.com
GENAI_API_KEY=your_api_key_here

# Model names:
# - When GENAI_PROVIDER=gemini: Gemini model names, e.g. gemini-3-pro-image-preview
# - When GENAI_PROVIDER=wan:    Wanxiang model names, e.g. wan2.5-t2i-preview / wan2.5-i2i-preview
GENAI_GEN_MODEL_NAME=gemini-3-pro-image-preview
GENAI_EDIT_MODEL_NAME=gemini-3-pro-image-preview

# Request timeout in seconds for each GenAI call (generate / edit)
GENAI_TIMEOUT_SECONDS=120

# Image output format:
# - base64: return image as data URI (base64 encoded)
# - url:    upload image to OSS and return plain URL
GENAI_IMAGE_FORMAT=base64

HTTP server

SERVER_ADDRESS=0.0.0.0
SERVER_PORT=8080

MCP endpoint will listen on:

http://SERVER_ADDRESS:SERVER_PORT/mcp

OSS / S3 configuration (optional, required when GENAI_IMAGE_FORMAT=url)

# For AWS S3: leave OSS_ENDPOINT empty or set to s3.amazonaws.com
# For Aliyun OSS: set to oss-cn-hangzhou.aliyuncs.com or your region
# For Tencent COS: set to cos.ap-guangzhou.myqcloud.com
# For MinIO: set to your MinIO endpoint
OSS_ENDPOINT=
OSS_REGION=us-east-1
OSS_ACCESS_KEY=your_access_key_here
OSS_SECRET_KEY=your_secret_key_here
OSS_BUCKET=your_bucket_name

When GENAI_IMAGE_FORMAT=url:

• For Aliyun OSS: make sure
  • OSS_ENDPOINT is like oss-cn-beijing.aliyuncs.com
  • The bucket policy allows read access if you expect the returned URL to be publicly accessible

---

3. Running the MCP Server

You can run the MCP server in two ways:

1. Clone & build from source

   • Clone this repo and enter the project root

   • Copy env.example to .env and fill in your configuration

   • Run:

     go build .
     ./genai-mcp
     

2. Download release binary

   • Download the appropriate binary from the Releases page

   • Place it in a directory of your choice

   • Copy env.example from this repo (or from the release asset) to .env in the same directory and update configuration

   • Run (binary name may vary by platform):

     ./genai-mcp
     

By default the MCP HTTP endpoint will be:

http://127.0.0.1:8080/mcp

You can connect to this MCP endpoint from any MCP‑compatible client (e.g. Code editors or tools that support the streamable HTTP MCP transport).

---

4. MCP Tools

The server registers two tools in internal/tools/gemini.go:

• gemini_generate_image

  • Input:
    • prompt (string, required): text prompt describing the image
  • Output:
    • When GENAI_IMAGE_FORMAT=base64: a data:image/...;base64,... string
    • When GENAI_IMAGE_FORMAT=url: an OSS/S3 URL generated by the server

• gemini_edit_image

  • Input:
    • prompt (string, required): how to edit the image
    • image_url (string, required): original image URL or data URI
  • Output:
    • Same format as above (base64 or url), depending on configuration

When GENAI_IMAGE_FORMAT=url:

• Generated / edited images are:
  • Downloaded (if Gemini returns a URL), or decoded (if it returns inline data)
  • Re‑uploaded to OSS / S3
  • Stored under key pattern: images/yyyy-MM-dd/{uuid_timestamp_random}.ext

---

5. Contact

• WeChat: Scan the QR code below to add as a friend

  

• Discord: Username adamydwang

---

Star History