transfer-ai-mcp
Provides tools for text generation and image generation via OpenAI-compatible API endpoints, allowing AI agents to generate text and images using configured models.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@transfer-ai-mcpGenerate an image of a futuristic city"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
transfer-ai-mcp
transfer-ai-mcp is a small MCP server for relay or proxy AI endpoints. It reads configuration from environment variables and exposes tools for text generation and image generation.
Features
Supports
openai-style andgemini-style HTTP APIsConfigurable
url,key, andmodelthrough environment variablesSaves generated images locally and returns file paths (no base64 in MCP response)
Packaged as a standalone Node library for reuse on other machines
Related MCP server: gemini-image-mcp
Changelog
v0.2.0
Fix:
generate_imageno longer returns base64 image data in MCP response. This fixes a crash in MCP clients (e.g. Kiro) that occurred when processing large image payloads in subsequent turns. Images are saved to disk and only file paths are returned.Change: Default
TRANSFER_AI_API_FORMATchanged fromopenaitogemini.Response now includes file size info for each saved image.
v0.1.0
Initial release.
Install
npm installFor a global install:
npm install -g .Then run:
transfer-ai-mcpEnvironment variables
Required:
TRANSFER_AI_API_KEYTRANSFER_AI_BASE_URLunless you useTRANSFER_AI_TEXT_URLandTRANSFER_AI_IMAGE_URLTRANSFER_AI_MODELunless you set bothTRANSFER_AI_TEXT_MODELandTRANSFER_AI_IMAGE_MODEL
Optional:
TRANSFER_AI_API_FORMATopenaiorgeminidefault:
gemini
TRANSFER_AI_AUTH_MODEbearer,query,x-goog-api-key, ornonedefault:
bearer
TRANSFER_AI_TEXT_MODELTRANSFER_AI_IMAGE_MODELTRANSFER_AI_TEXT_URLTRANSFER_AI_IMAGE_URLTRANSFER_AI_TEXT_PATHTRANSFER_AI_IMAGE_PATHTRANSFER_AI_OUTPUT_DIR
Default endpoint behavior
If TRANSFER_AI_API_FORMAT=openai:
text requests default to
/v1/chat/completionsimage requests default to
/v1/chat/completions
If TRANSFER_AI_API_FORMAT=gemini:
text requests default to
/v1beta/models/{model}:generateContentimage requests default to
/v1beta/models/{model}:generateContent
Override any of these with TRANSFER_AI_TEXT_URL, TRANSFER_AI_IMAGE_URL, TRANSFER_AI_TEXT_PATH, or TRANSFER_AI_IMAGE_PATH.
Tools
get_configuration_statusgenerate_textgenerate_imageget_last_image_info
generate_text arguments:
promptsystemPromptmodeltemperaturemaxTokensextraBody
generate_image arguments:
promptsystemPromptmodelaspectRatioimageSizeoutputPathextraBody
Kiro / VS Code MCP example
{
"mcpServers": {
"transfer-ai": {
"command": "node",
"args": ["/path/to/transfer-ai-mcp/dist/index.js"],
"env": {
"TRANSFER_AI_API_FORMAT": "gemini",
"TRANSFER_AI_AUTH_MODE": "bearer",
"TRANSFER_AI_API_KEY": "your-api-key",
"TRANSFER_AI_BASE_URL": "https://your-endpoint.example.com",
"TRANSFER_AI_MODEL": "gemini-2.0-flash-preview-image-generation",
"TRANSFER_AI_OUTPUT_DIR": "/path/to/output/images"
},
"disabled": false,
"autoApprove": ["generate_image", "get_configuration_status"]
}
}
}Codex MCP example
This server cannot be deployed
Maintenance
Related MCP Connectors
MCP server for OpenAI API (chat completions, image generation, embeddings) via AceDataCloud
MCP server for AI dialogue using various LLM models via AceDataCloud
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