The confluence2md Platform

July 9, 2026 · View on GitHub

Three tools that together form a complete local Confluence knowledge pipeline — from raw pages to AI-queryable search.

Overview

ToolRole
confluence2mdCrawls Confluence and exports pages as local Markdown files
confluence2md-indexerIndexes the Markdown export into a searchable SQLite database
confluence2md-mcpExposes the index to AI clients via the Model Context Protocol

Architecture

Platform diagram

Data Flow

1. Crawl — confluence2md

Authenticates to Confluence via the REST API, fetches pages and attachments, converts HTML to Markdown, and writes one .md file per page with stable filenames and deterministic YAML front matter. Produces a metadata.json link graph and an index.md start page.

2. Index — confluence2md-indexer

Reads the Markdown output directory, chunks each page, computes vector embeddings, builds FTS tables, and stores everything in a single local SQLite file. Supports lexical (BM25), vector (cosine), and hybrid retrieval. Can also be used as a Go library via its public Query API.

3. Serve — confluence2md-mcp

Wraps confluence2md-indexer as a stdio MCP server. Receives search queries from any MCP-compatible AI client (VS Code Copilot, Claude Code, OpenAI Codex, etc.), queries the SQLite index with hybrid retrieval, and returns ranked results with score metadata.

Quick Start

# 1. Crawl your Confluence space
confluence2md --config config.yaml

# 2. Build the search index
confluence2md-indexer index ./output

# 3. Configure your AI client to use the MCP server
#    (see confluence2md-mcp README for VS Code / Claude Code setup)