Auto-loads skills into agent sessions. MiniMax vision and search proxy.
{
"mcpServers": {
"io-github-divitkashyap-auto-skill-loader": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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Auto-loads skills into agent sessions. MiniMax vision and search proxy.
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
License not specified.
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Commit history unknown.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
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Give your AI agent a persistent skill library it auto-loads at session start.
⚠️ OpenCode image workflow note (April 2026): OpenCode has two issues with images via MCP: (1) its stdio transport for local MCP servers is broken (causes "login fail" errors) — our proxy tools work around this, but (2) pasted images render visually but don't expose real file paths to tools (they appear as filenames). For images in OpenCode, you must give an actual file path rather than pasting. Claude Code doesn't have either of these issues.
Core value prop: This tool was built so skills auto-load at session start in OpenCode — no manual
use_skillinvocation needed. The proxy tools (vision + web search) are a bonus. If you only need vision in Claude Code, useminimax-token-plandirectly instead.
mcp-name: io.github.divitkashyap/auto-skill-loader
~/.config/auto-skill-loader/config.yamlskills://activeskills://active and gets all approved skills auto-injectedThe main problem: In OpenCode, skills don't auto-load — the agent has to explicitly invoke them or rely on unreliable fuzzy matching. auto-skill-loader solves this by exposing your skill library as an MCP resource that gets read at session start. Deterministic, no guessing.
Bonus: Our proxy tools also work around OpenCode's broken MCP stdio transport for the MiniMax vision and web search tools.
uvx auto-skill-loader
pip install auto-skill-loader
auto-skill-loader
git clone https://github.com/divitkashyap/auto-skill-loader.git
cd auto-skill-loader
pip install -e .
auto-skill-loader
Add to ~/.config/opencode/opencode.json:
{
"mcp": {
"auto-skill-loader": {
"type": "local",
"command": ["uvx", "auto-skill-loader"],
"enabled": true
}
}
}
Note: Claude Code requires a specific JSON format via add-json:
claude mcp add-json -s user auto-skill-loader '{"type":"stdio","command":"/FULL/PATH/TO/python","args":["-m","server"],"env":{"MINIMAX_TOKEN_PLAN_KEY":"sk-cp-YOUR-KEY-HERE"}}'
Replace /FULL/PATH/TO/python with the path to your Python (e.g. /Users/YOU/auto-skill-loader/.venv/bin/python).
Or for uvx (requires network on first run):
claude mcp add -s user --transport stdio -e MINIMAX_TOKEN_PLAN_KEY=sk-cp-YOUR-KEY auto-skill-loader -- uvx auto-skill-loader
| Host | Skill Auto-Load | Vision Proxy | Image Paste | Notes |
|---|---|---|---|---|
| Claude Code (macOS) | ✅ | ❌ Not needed | ✅ | Use minimax-token-plan MCP directly instead |
| OpenCode (macOS) | ✅ | ✅ Works | ❌ Broken | Give file paths instead of pasting |
Skill auto-loading confirmed working on both hosts. The vision proxy bypasses OpenCode's broken stdio transport, but image paste-to-path is a separate rendering issue in OpenCode that requires using file paths.
Other MCP-compatible hosts (Cursor, Zed, etc.) should work with the same configuration — contributions welcome.
Both hosts work with auto-skill-loader vision tools, but image input behaves differently:
| Host | How images are passed | Recommended workflow |
|---|---|---|
| Claude Code | Images uploaded to URL automatically → tool receives URL | Paste image directly ✅ works |
| OpenCode | Inline images render visually but may not give tools a real path | Give a file path instead of pasting |
OpenCode note: When you paste an image in OpenCode, it may ren