quartz-sharepoint-mcp

An MCP server that mirrors a SharePoint document library to disk and lets AI assistants search it via the Model Context Protocol.

How it works

1. On startup, all files under your configured SharePoint path are downloaded locally.

2. A background thread polls Microsoft Graph for changes every POLL_INTERVAL seconds, keeping the mirror in sync.

3. A single MCP tool — search_sharepoint(query) — runs opencode against the local files and returns the result.

SharePoint (Graph API) → local mirror → opencode → MCP client

Related MCP server: MCP Document Indexer

Prerequisites

• Python 3.11+

• opencode in your PATH

• An Azure AD App Registration with Sites.Read.All (or equivalent) granted as an application permission

Setup

# 1. Install dependencies
pip install -r requirements.txt

# 2. Configure environment
cp .env.example .env
# Fill in your Azure and SharePoint credentials

# 3. Run
python server.py

The server starts on http://0.0.0.0:8001 by default.

Environment variables

Endpoints

MCP tool

search_sharepoint — accepts a natural-language query, runs it against the local mirror via opencode, and returns the answer as plain text.

To connect from an MCP client:

{
  "mcpServers": {
    "sharepoint": {
      "url": "http://localhost:8001/mcp",
      "headers": { "Authorization": "Bearer <your-token>" }
    }
  }
}

Admin panel

Visit http://localhost:8001 to manage bearer tokens — create, enable/disable, or revoke access without restarting the server.