MCP Servers

kb-mcp

Semantic search MCP server for Acumatica KB Obsidian vault, enabling querying and reading knowledge base files via natural language.

README

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

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