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MCP server · AI

Genai MCP

Nano Banana MCP Server: Free Gemini/Tongyi Image Gen MCP Server for AI Workflows

Unclaimed Apache-2.0 last commit 10 months ago genaiscriptmcpmcp-server
59Fair

Scored 7 days ago · breakdown

About Genai MCP

Genai MCP is an MCP server published by adamydwang in the AI category: nano Banana MCP Server: Free Gemini/Tongyi Image Gen MCP Server for AI Workflows.

The repository has 3 stars and 0 forks, with the last commit 10 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/adamydwang/genai-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 22 hours ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

release/0.3v0.3 · 8 Dec 2025Supported Providers: gemini: google official and dmxapi backend wan: Tongyi Wanxiang official apimart
release/0.2v0.2 · 4 Dec 2025Support Models: Gemini: Nana Banana / Nana Banana Pro Tongyi Wanxiang `env.example`: GenAI MCP Server Configuration Copy this file to .env and fill in your actual values GenAI Provider Supported values: gemini: use Google Gemini /…
release/0.1v0.1 · 3 Dec 2025Support model: nano banana nano banana pro Support function: generate image edit image Api backend: googleapi dmxapi

README

GenAI MCP Server

This project implements a Model Context Protocol (MCP) server for image generation and image editing using Google Gemini, Tongyi Wanxiang, 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, Wan, and APIMart.

Provider matrix

Provider Supported Models Config Notes
google · gemini-3-pro-image-preview · gemini-2.5-flash-image GENAI_PROVIDER=geminiGENAI_BASE_URL=https://generativelanguage.googleapis.com Official Gemini
dmxapi · gemini-3-pro-image-preview · gemini-2.5-flash-image GENAI_PROVIDER=geminiGENAI_BASE_URL=https://www.dmxapi.cn Gemini‑compatible gateway
aliyun · wan2.5-i2i-preview · wan2.5-t2i-preview GENAI_PROVIDER=wanGENAI_BASE_URL=https://dashscope.aliyuncs.com Tongyi Wanxiang
apimart · gemini-3-pro-image-preview GENAI_PROVIDER=apimartGENAI_BASE_URL=https://api.apimart.ai APIMart Gemini wrapper (cost‑effective)

1. Prerequisites

  • Go 1.21+ (recommended)
  • A valid Gemini (or provider) 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
# - apimart: APIMart (Gemini-wrapped async image APIs)
GENAI_PROVIDER=gemini

# Shared GenAI endpoint / key for all 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
# - When GENAI_PROVIDER=apimart: Gemini image model name, e.g. gemini-3-pro-image-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:

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: ensure OSS_ENDPOINT like oss-cn-beijing.aliyuncs.com and bucket policy allows expected read access.

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 repo or release asset) to .env and update configuration

    • Run (binary name may vary by platform):

      ./genai-mcp
      

Default MCP HTTP endpoint:

http://127.0.0.1:8080/mcp

Connect from any MCP‑compatible client supporting streamable HTTP transport.


4. MCP Tools

Gemini tools (internal/tools/gemini.go)

  • gemini_generate_image

    • Input: prompt (string, required)
    • Output: base64 data URI or URL (optional OSS upload)
  • gemini_edit_image

    • Input: prompt (required), image_urls (required, JSON array)
    • Output: base64 data URI or URL

When GENAI_IMAGE_FORMAT=url, images are downloaded/decoded then uploaded to OSS/S3 under images/yyyy-MM-dd/{uuid_timestamp_random}.ext.

Wan tools (internal/tools/wan.go)

  • wan_create_generate_image_task
  • wan_query_generate_image_task
  • wan_create_edit_image_task
  • wan_query_edit_image_task

Wan is async; create a task then poll for completion.

APIMart tools (internal/tools/apimart.go)

  • apimart_create_generate_image_task
  • apimart_query_generate_image_task
  • apimart_create_edit_image_task
  • apimart_query_edit_image_task

APIMart is async; tools return the final image (URL or base64) once the task is completed.


5. Contact


Star History

Star History Chart

README fetched from the repository 22 hours ago. The original is authoritative.

Questions

About Genai MCP

How do I install Genai MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Genai MCP safe to use with an AI agent?

Its trust score is 59 out of 100 (fair). It passes 5 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Genai MCP still maintained?

The last commit was 10 months ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.