kb-mcp
Semantic search MCP server for the Acumatica KB Obsidian vault. Reuses the embeddings already computed by the Smart Connections plugin (TaylorAI/bge-micro-v2, 384-dim).
Tools
| Tool | What it does |
|---|---|
search_kb(query, top_k, source_only, guide_filter) |
Semantic search — embed query, cosine-search ~89k vectors, return top results with snippet |
read_kb_file(path) |
Read full content of a KB file by relative path |
Setup
1. Install
cd path\to\kb-mcp
python -m venv .venv
.venv\Scripts\activate
pip install -e .
2. Build the index (run once, ~2 min)
# with .venv active, from the kb-mcp folder:
set KB_VAULT_DIR=path\to\Acumatica-KB
python -m kb_mcp.build_index
This creates kb_index.npy and kb_meta.json inside src\kb_mcp\. Re-run only if you add new notes to the vault (and re-index in Obsidian Smart Connections first).
3. Register with Claude Desktop
Add to claude_desktop_config.json (found at %APPDATA%\Claude\claude_desktop_config.json):
{
"mcpServers": {
"kb-mcp": {
"command": "C:\\path\\to\\kb-mcp\\.venv\\Scripts\\python.exe",
"args": ["-m", "kb_mcp.server"],
"env": {
"KB_VAULT_DIR": "C:\\path\\to\\Acumatica-KB"
}
}
}
}
Restart Claude after adding.
4. First query (model download)
The TaylorAI/bge-micro-v2 model (~45 MB) downloads automatically on the first search_kb call and is cached locally by HuggingFace.
Environment variables
| Variable | Default | Description |
|---|---|---|
KB_VAULT_DIR |
auto-detected | Path to the Acumatica-KB vault folder |
KB_MCP_INDEX_DIR |
src/kb_mcp/ |
Where kb_index.npy and kb_meta.json live |
KB_SNIPPET_LINES |
30 |
Lines to include in each result snippet |
