A **SensorMCP Model Context Protocol (MCP) Server** that enables automated dataset creation and custom object detection model training through
If you already use Sensor MCP, the sensor mcp mcp server is the piece that lets your assistant work with it directly. A SensorMCP Model Context Protocol (MCP) Server that enables automated dataset creation and custom object detection model training through natural language interactions. This project integrates computer vision capabilities with Large.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
Prerequisites — The Prerequisites tool exposed by this serverSetup — 1. Clone the repository: bash git clone cd sensor-mcpSetup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Configuration is passed through the environment: UNSPLASH_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
uv python install 3.13) - CUDA-compatible GPU (recommended for training)Plenty of developer tooling servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Sensor MCP's toolset — Prerequisites, Setup — is a fair guide to whether it matches your workflow. It is maintained by sensormcp; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Sensor MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Prerequisites | The Prerequisites tool exposed by this server. |
| Setup | 1. **Clone the repository**: bash git clone <repository-url> cd sensor-mcp |
{
"mcpServers": {
"sensormcp-server": {
"type": "stdio",
"command": "uv",
"args": [
"--directory",
"/path/to/sensor-mcp",
"run",
"src/zoo_mcp.py"
]
}
}
}Configuration as documented by the project. Restart the client after saving.
uv python install 3.13) - CUDA-compatible GPU (recommended for training)| Variable | Description | Required |
|---|---|---|
| UNSPLASH_API_KEY | Credential the server authenticates with. | Yes |
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Microsoft's official browser automation server — drive a real browser through the accessibility tree, no screenshots needed.
GitHub's official server — repos, issues, pull requests, Actions and code security, straight from your assistant.
Issue tracking at the speed of conversation — Linear's official hosted server with OAuth and zero install.
Local repository surgery — status, diffs, commits, branches and history for any repo on disk.
Timezone sanity for AI — current time anywhere and correct conversions, without the model doing date math.