DeepSeek Vision Bridge

DeepSeek Vision Bridge

Bridges text-only AI models to Google Gemini for image analysis, providing structured visual descriptions, object detection, and answers to image-based questions via MCP.

Category
Visit Server

README

DeepSeek Vision Bridge

A visual perception bridge enabling text-only AI models (such as DeepSeek) to see and read images via Google Gemini.

When sending images to a model that lacks vision capabilities, this tool automatically forwards the image to Gemini for visual analysis and returns structured text results for the AI model to process.


Prerequisites


Installation

Step 1: Clone the Repository

Open PowerShell (press Win + R, type powershell, and press Enter) and run:

git clone https://github.com/tqctqc1/deepseek-vision-mcp.git
cd deepseek-vision-mcp

If Git is not installed, download it from git-scm.com or click Code -> Download ZIP on GitHub, extract it, and open PowerShell inside the folder.

Step 2: Install Dependencies & Bootstrap (Self-Healing)

Run the one-command bootstrap script in PowerShell:

powershell -ExecutionPolicy Bypass -File .\ensure_env.ps1

Or via CLI:

python vision_cli.py --setup

This automatically creates .venv, installs dependencies, sets up .env, and verifies environment health.

Check environment health (<1s check):

python vision_cli.py --health --pretty

Step 3: Configure API Key

Copy-Item .env.example .env

Open .env in Notepad and replace put-your-key-here with your Gemini API key:

GEMINI_API_KEY=AIzaSy...your-api-key...

Save the file. Do not share your .env file publicly.


Usage

Option 1: Command-Line Interface (CLI)

Analyze a local image:

python vision_cli.py --image-path "C:\path\to\image.png" --question "Describe the contents of this image." --pretty

Analyze an image from a URL:

python vision_cli.py --image-url "https://example.com/image.jpg" --question "Transcribe text in this image." --pretty

Option 2: Integration with Claude Desktop (plugin marketplace)

This repository is a Claude plugin marketplace. In Claude Desktop:

  1. Open Settings -> Plugins -> Add marketplace and paste: https://github.com/tqctqc1/deepseek-vision-mcp
  2. Click Sync, then install the deepseek-vision plugin.
  3. Claude copies the plugin to a managed directory. Run the 1-command bootstrap inside that plugin directory:
    powershell -ExecutionPolicy Bypass -File .\ensure_env.ps1
    
    Then put your Gemini API key in .env.
  4. Restart Claude Desktop and confirm the vision_analyze tool appears.

Requires python to be on your PATH. If you prefer manual MCP configuration instead, follow Option 3.

Option 3: Integration with Claude Desktop (manual MCP)

Open the Claude Desktop configuration file:

notepad "$env:APPDATA\Claude\claude_desktop_config.json"

Add the following under mcpServers (update the paths to match your installation directory):

{
  "mcpServers": {
    "deepseek-vision": {
      "command": "C:\\path\\to\\deepseek-vision-mcp\\.venv\\Scripts\\python.exe",
      "args": ["C:\\path\\to\\deepseek-vision-mcp\\server.py"],
      "env": { "PYTHONUTF8": "1" }
    }
  }
}

Save the file, exit Claude Desktop completely, and reopen it.

Option 4: Integration with Codex

Install the marketplace, then the plugin:

codex marketplace add tqctqc1/deepseek-vision-mcp
codex plugin install deepseek-vision@deepseek-vision-mcp

The Codex plugin bundles skills that tell the agent to use the vision_analyze MCP tool, with a CLI fallback (vision_cli.py) when the MCP server is unavailable. Like other marketplace installs, the plugin cache does not include a venv — create it in the installed plugin directory if the CLI fallback is needed:

python -m venv --system-site-packages "$env:USERPROFILE\.codex\plugins\cache\deepseek-vision-mcp\deepseek-vision\1.0.0\.venv"

Output Format

The tool returns a JSON object containing 4 fields:

Field Description
answer Direct answer to your question
description Comprehensive visual description of the image
objects List of detected objects
uncertainties Ambiguities or low-confidence details

Supported Image Formats

PNG, JPEG, WebP, HEIC, HEIF — up to 10 MB.


Troubleshooting

Error Solution
GEMINI_API_KEY is not configured Verify your .env file contains a valid API key
Image file does not exist Double check the image path
python is not recognized Reinstall Python and make sure to check "Add to PATH"
Claude Desktop says "This repository isn't a marketplace" Make sure you added the marketplace URL https://github.com/tqctqc1/deepseek-vision-mcp (the .claude-plugin/marketplace.json manifest lives at the repo root)
Claude Desktop does not show the tool Verify config paths / setup steps and restart Claude Desktop
MCP tool vision_analyze is missing The plugin MCP server failed to start — run the venv setup in the installed plugin directory and confirm .env exists there

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured