WSO2 Docs MCP Server

"This is an unofficial community project. Not affiliated with or endorsed by WSO2."

A production-ready Model Context Protocol (MCP) server that provides AI assistants (Claude Desktop, Claude Code, Cursor, VS Code) with semantic search over WSO2 documentation via Retrieval-Augmented Generation (RAG).

Under the hood, it uses a blazing-fast dual-ingestion engine:

• GitHub Native: Fetches raw Markdown directly from WSO2's public GitHub repositories via the Git Trees API (avoids web-scraping noise and rate limits)
• Web Crawl Fallback: For products without dedicated GitHub docs repos (like the WSO2 Library)

Architecture

Documentation Sources

Prerequisites

• Node.js ≥ 20
• Docker (for pgvector)
• Embeddings - no API key required by default:
  • Ollama (recommended) - runs locally, model auto-downloaded on first run
  • If Ollama is not running, the server automatically falls back to HuggingFace ONNX (in-process, also downloads automatically)
  • Cloud providers are also supported: OpenAI, Google Gemini, Voyage AI

Quick Start

Choose the setup path that fits your use case:

• Install from npm - simplest, no cloning required
• Clone and build - for development or contributions

Install from npm

Install the package globally to get the wso2-docs-mcp-server, wso2-docs-crawl, and wso2-docs-migrate commands available system-wide:

npm install -g wso2-docs-mcp-server

Prefer no global install? You can use npx wso2-docs-mcp-server, npx wso2-docs-crawl, and npx wso2-docs-migrate in every step below - just replace the bare command with its npx equivalent.

1. Start pgvector

Download the docker-compose.yml and start the database:

curl -O https://raw.githubusercontent.com/iamvirul/wso2-docs-mcp-server/main/docker-compose.yml
docker compose up -d

2. Start Ollama (optional but recommended)

Install Ollama and pull the default embedding model:

ollama pull nomic-embed-text
ollama serve

No Ollama? Skip this step. The server automatically falls back to HuggingFace ONNX - model downloads on first use with no extra setup.

3. Run database migration

DATABASE_URL="postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs" \
  wso2-docs-migrate

Run migration again whenever you change EMBEDDING_DIMENSIONS (i.e. switch embedding provider). The script detects and handles dimension changes automatically.

4. Index WSO2 documentation

# Index all products (first run downloads the embedding model automatically)
DATABASE_URL="postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs" \
  wso2-docs-crawl

# Index a single product (faster, great for testing)
DATABASE_URL="postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs" \
  wso2-docs-crawl --product ballerina --limit 20

# Force re-index even unchanged pages
DATABASE_URL="postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs" \
  wso2-docs-crawl --force

Available product IDs: apim, mi, bi, choreo, is, ballerina, library

5. Configure your AI client

T

... View full README on GitHub