Species Identification Mcp
About
An MCP (Model Context Protocol) server that identifies biological species from images, returning Latin names with confidence scores.
Details
- Author
- fonkychen
- Downloads
- 259
- Categories
- Other
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- Identifies species from images (plants, animals, fungi, insects, etc.)
- Returns Latin scientific names with confidence scores
- Designed for LLM tool usage via Model Context Protocol (MCP)
- Simple stdio‑based MCP server
- Easy to run with npx
- API key managed via environment variables
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Species Identification McpCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install via npm install, then configure the server in your MCP client using the command npx -y nature-vision-mcp and set the environment variable NATURE_VISION_API_KEY. A dummy token (app-dummy-token-2026) is provided for testing, allowing one request per minute.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"species identification mcp": {
"nature-vision": {
"command": "npx",
"args": [
"-y",
"nature-vision-mcp"
],
"env": {
"NATURE_VISION_API_KEY": "xxx"
}
}
}
}
}Mcp.servers
{
"nature-vision": {
"command": "npx",
"args": [
"-y",
"nature-vision-mcp"
],
"env": {
"NATURE_VISION_API_KEY": "xxx"
}
}
}\# Nature Vision MCP Server
An \\MCP (Model Context Protocol) server\\ that identifies biological species from images using the \\Nature Vision API\\, returning Latin names with confidence scores.
This server enables LLMs (such as Claude) to recognize species and enrich responses with biological knowledge.
---
\## Features
\- 🌿 Identify species from images (plants, animals, fungi, insects, etc.)
\- 🧬 Returns \\Latin scientific names\\ with confidence scores
\- 🧠 Designed for \\LLM tool usage\\ via Model Context Protocol (MCP)
\- 🔌 Simple stdio-based MCP server
\- 🚀 Easy to run with npx
\- 🔐 API key via environment variables
---
\## Supported Categories
\- plant
\- bug
\- bird
\- mammal
\- reptile
\- amphibian
\- mollusc
\- fungi
---
\## Installation
``bash`
npm install
\\Configure in your MCP client:\\
json`
{
"mcp.servers": {
"nature-vision": {
"command": "npx",
"args": ["-y", "nature-vision-mcp"],
"env": {
"NATURE_VISION_API_KEY": "app-xxx"
}
}
}
}
For now, you can use token: app-dummy-token-2026, this will allow you request once per minute.
"NATURE_VISION_API_KEY": "app-dummy-token-2026"
npx nature-vision-mcp
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