opencode-eyes-nvidia
Eyes for models that cannot see — on NVIDIA NIM. Any of seven hosted
vision models (MiniMax-M3 by default), with multi-key rotation when one key is
rate-limited.
给不具备多模态能力的模型一双眼睛:走 NVIDIA NIM,默认 MiniMax-M3,支持多 Key 轮换。
As a DeepSeek Harness plugin: the MCP server ships inside the bundle, so
installing one plugin is the whole setup — no mcpServers file to hand-edit.
Install
DeepSeek Harness Desktop — open Plugins in the sidebar, choose Add
plugin, and enter:
https://github.com/bauerelizabeth07139/opencode-eyes-nvidia
Then switch the new dsh-opencode-eyes-nvidia bundle on. The Desktop app boots the
reserved desktop profile, so that is where it has to be enabled.
dsh CLI — install it into the profile you actually boot:
dsh plugin --profile web add bauerelizabeth07139/opencode-eyes-nvidia
No git on the machine? pnpm resolves a git shorthand with git ls-remote,
which fails with 'git' is not recognized when git is missing. Use the tarball
instead — that path is plain HTTPS:
dsh plugin --profile web add https://codeload.github.com/bauerelizabeth07139/opencode-eyes-nvidia/tar.gz/main
The same address works in the Desktop Add plugin dialog. Replace main
with a commit SHA to pin an exact revision (/tar.gz/<sha>).
Uninstall with dsh plugin --profile web remove dsh-opencode-eyes-nvidia.
Requirements
- Python ≥ 3.8 on
PATH, or pointed at with python.
- Pillow in that interpreter — the server's only third-party import
(
pip install Pillow).
- At least one NVIDIA API key. The server accepts
NVIDIA_API_KEY,
NVIDIA_API_KEYS (several, separated by spaces/commas/semicolons) or
NVIDIA_API_KEY_1..N, and rotates through them on failure. describe_image
needs one; list_vision_models works without.
Tools
The server registers 2 tool(s). DSH namespaces them automatically,
so the model calls them as mcp__opencode_eyes_nvidia__<tool>:
| Tool | What it does |
|---|
describe_image | Sends an image to the chosen NVIDIA-hosted vision model. Parameters: image_path (required), prompt (optional), model (optional; one of minimaxai/minimax-m3, meta/llama-3.2-11b-vision-instruct, meta/llama-3.2-90b-vision-instruct, nvidia/llama-3.1-nemotron-nano-vl-8b-v1, google/gemma-3-27b-it, nvidia/nemotron-nano-12b-v2-vl, qwen/qwen3.5-397b-a17b). |
list_vision_models | Returns the model list, consulting the live /models endpoint when a key is present. |
Configuration
| Key | Environment variable | Default | Meaning |
|---|
python | — | discovered | interpreter that runs the server |
apiKey | NVIDIA_API_KEY | (empty) | the first key of the rotation ring |
model | NVIDIA_MODEL | minimaxai/minimax-m3 | default model id |
baseUrl | NVIDIA_BASE_URL | https://integrate.api.nvidia.com/v1 | NIM endpoint |
timeoutSeconds | NVIDIA_TIMEOUT | 120 | the server's own HTTP timeout |
maxDimension | NVIDIA_MAX_DIMENSION | 2048 | images are downscaled to this edge length |
jpegQuality | NVIDIA_JPEG_QUALITY | 85 | JPEG quality of the re-encoded image |
thinkingMode | NVIDIA_THINKING_MODE | (unset) | enabled / disabled / adaptive; only sent to minimax models |
toolCallTimeoutMs | — | 300000 | DSH's per-call budget; key rotation sleeps between attempts |
env | — | {} | raw passthrough — use this for NVIDIA_API_KEYS and NVIDIA_API_KEY_1..N |
Every field is optional and lives in the loader row. For example, in
cordis.patch.yml:
- id: dsh-opencode-eyes-nvidia
name: 'dsh-opencode-eyes-nvidia'
config:
apiKey: 'nvapi-...'
model: 'minimaxai/minimax-m3'
env:
NVIDIA_API_KEYS: 'nvapi-first,nvapi-second'
Notes
-
Rotating several keys. config.apiKey sets NVIDIA_API_KEY; to use the
rotation ring, pass the extra variables through config.env:
config:
env:
NVIDIA_API_KEYS: 'nvapi-first,nvapi-second'
NVIDIA_ROTATION_BACKOFF: '2'
-
Timeouts. A call may try several keys with a 2 s backoff between attempts,
on top of the server's own 120 s HTTP timeout — the plugin mounts with a
300 s budget.
-
thinkingMode is silently ignored unless the model id contains
minimax, which is the server's own rule.
How it is mounted
index.js resolves a Python interpreter (the configured python, then
python3/python on PATH), hands the server its argv and working directory,
and mounts it as a stdio MCP server through @deepseek-ai/dsh-mcp-client with
failOnStartupError: true, so a server that cannot start is a visible error
rather than a silently missing tool.
Credentials are forwarded explicitly. The harness scrubs credential-shaped
variables (KEY, TOKEN, SECRET, PASSWORD) out of the environment a child
process inherits, so config.apiKey — falling back to the variable the server
documents — is written into the child's environment by the plugin itself. That
means both of these work:
config:
apiKey: '<your key>'
export NVIDIA_API_KEY='<your key>' # picked up at load time
Development
No build step and no runtime dependencies — @deepseek-ai/cordis and
@deepseek-ai/dsh-mcp-client are peers supplied by the Harness.
npm test # node >= 22: manifest checks + the stdio mount, both Harness-free
The mount test loads index.js with @deepseek-ai/dsh-mcp-client stubbed and
asserts the exact stdio configuration the plugin produces, including the
credential forwarding above.
Repository layout
| Path | Purpose |
|---|
index.js | the DSH plugin: resolves the interpreter and mounts the server |
cordis.patch.yml | the loader row that activates the plugin |
locale/{en,zh}.json | card title and description for the plugin lists |
assets/icon.svg | card artwork |
test/ | npm test: manifest composition and the mount contract |
src/opencode_eyes_nvidia/ | the MCP server, unchanged |
pyproject.toml, requirements.txt | the Python package metadata, unchanged |
Other hosts (unchanged)
The server is a plain stdio MCP server and still works anywhere else. The
repository's original README is kept verbatim as
README.opencode.md, and the launch stanza from it keeps
working:
{
"mcp": {
"opencode-eyes-nvidia": {
"type": "local",
"command": ["python", "-m", "opencode_eyes_nvidia"],
"enabled": true,
"timeout": 120000,
"environment": {
"NVIDIA_API_KEYS": "{env:NVIDIA_API_KEYS}",
"NVIDIA_API_KEY": "{env:NVIDIA_API_KEY}"
}
}
}
}
On another host, run the server from the repository's src directory (or put
src on PYTHONPATH).
License
MIT — the repository declared MIT in pyproject.toml but shipped no licence file; this plugin's release adds one.
