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คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
npx -y [email protected]Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
DATABASE_URL=<value> EMBEDDING_PROVIDER=<value> OPENAI_API_KEY=<secret> GEMINI_API_KEY=<secret> VOYAGE_API_KEY=<secret> claude mcp add io.github.iamvirul-wso2-docs-mcp-server -- npx -y wso2-docs-mcp-server@1.3.16รันในเทอร์มินัล
{ "mcpServers": { "io.github.iamvirul-wso2-docs-mcp-server": { "command": "npx", "args": [ "-y", "[email protected]" ], "env": { "DATABASE_URL": "<value>", "EMBEDDING_PROVIDER": "<value>", "OPENAI_API_KEY": "<secret>", "GEMINI_API_KEY": "<secret>", "VOYAGE_API_KEY": "<secret>" } } }}claude_desktop_config.json
URL แบบรีโมตหรือคำสั่งบนเครื่องของคุณ? การติดตั้งสองแบบต่างกันอย่างไร
รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดจากผู้เผยแพร่
"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).
Semantic search over WSO2 docs (APIM, IS, MI, Choreo, Ballerina) via RAG and pgvector.
Under the hood, it uses a blazing-fast dual-ingestion engine:
Choose the setup path that fits your use case:
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, andnpx wso2-docs-migratein every step below - just replace the bare command with itsnpxequivalent.
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
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.
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.
# 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
The MCP server is launched on demand by your AI client - no background process needed.
Claude Desktop - edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"wso2-docs": {
"command": "wso2-docs-mcp-server",
"env": {
"DATABASE_URL": "postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs",
"EMBEDDING_PROVIDER": "ollama"
}
}
}
}
Claude Code - run once in your terminal:
claude mcp add wso2-docs \
--transport stdio \
-e DATABASE_URL="postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs" \
-e EMBEDDING_PROVIDER="ollama" \
-- wso2-docs-mcp-server
# Verify
claude mcp list
Cursor - create .cursor/mcp.json in your project root:
{
"mcpServers": {
"wso2-docs": {
"command": "wso2-docs-mcp-server",
"env": {
"DATABASE_URL": "postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs",
"EMBEDDING_PROVIDER": "ollama"
}
}
}
}
VS Code - create .vscode/mcp.json:
{
"servers": {
"wso2-docs": {
"type": "stdio",
"command": "wso2-docs-mcp-server",
"env": {
"DATABASE_URL": "postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs",
"EMBEDDING_PROVIDER": "ollama"
}
}
}
}
Using
npxinstead of global install? Replace"command": "wso2-docs-mcp-server"with"command": "npx"and add"args": ["-y", "wso2-docs-mcp-server"].
Cloud embedding provider? Add the key to
env, e.g."EMBEDDING_PROVIDER": "openai", "OPENAI_API_KEY": "sk-...".
git clone https://github.com/iamvirul/wso2-docs-mcp-server.git
cd wso2-docs-mcp-server
npm install
Install Ollama and start it:
ollama serve
No Ollama? Skip this step. The server detects Ollama is not running and automatically falls back to HuggingFace ONNX inference - the model downloads on first use with no extra setup.
cp .env.example .env
# Defaults work out of the box with Ollama.
# Only edit if using a cloud provider (OpenAI / Gemini / Voyage).
docker compose up -d
# pgAdmin available at http://localhost:5050 ([email protected] / admin)
npm run db:migrate
Note: Run migration again whenever you change
EMBEDDING_DIMENSIONS(i.e. switch embedding provider). The script detects and handles dimension changes automatically.
# Index all products
# On first run the embedding model is downloaded automatically (Ollama or HuggingFace)
npm run crawl
# Index a single product (faster, great for testing)
npm run crawl -- --product ballerina --limit 20
# Force re-index even unchanged pages
npm run crawl -- --force
npm run build
npm start
For development (no build step):
npm run dev
Replace
/ABSOLUTE/PATH/TO/wso2-docs-mcp-serverwith your actual clone path.
Claude Desktop - edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"wso2-docs": {
"command": "node",
"args": ["/ABSOLUTE/PATH/TO/wso2-docs-mcp-server/dist/src/index.js"],
"env": {
"DATABASE_URL": "postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs",
"EMBEDDING_PROVIDER": "ollama"
}
}
}
}
Claude Code:
claude mcp add wso2-docs \
--transport stdio \
-e DATABASE_URL="postgresql://wso2mcp:wso2mcp@localhost:5432/wso2docs" \
-e EMBEDDING_PROVIDER="ollama" \
-- node "/ABSOLUTE/PATH/TO/wso2-docs-mcp-server/dist/src/index.js"
# Verify
claude mcp list
See config-examples/claude_code.sh for a convenience script.
Cursor - create .cursor/mcp.json - see config-examples/cursor_mcp.json.
VS Code - create .vscode/mcp.json - see config-examples/vscode_mcp.json.
[
{
"title": "Deploying WSO2 API Manager",
"snippet": "WSO2 API Manager can be deployed in various topologies…",
"source_url": "https://apim.docs.wso2.com/en/latest/install-and-setup/...",
"product": "apim",
"section": "Deployment Patterns",
"score": 0.8712
}
]
The default EMBEDDING_PROVIDER=ollama runs entirely on your machine with no API key. The startup sequence is:
Is Ollama running?
├── Yes → Is model present?
│ ├── Yes → Ready (instant)
│ └── No → Pull via Ollama (streamed, runs once)
└── No → Download ONNX model from HuggingFace Hub (~250 MB, cached after first run)
and run inference in-process via @huggingface/transformers
Both paths use nomic-embed-text / Xenova/nomic-embed-text-v1 by default and produce identical 768-dim vectors, so you can switch between them without re-indexing.
When Ollama is not available, the server auto-detects the best compute backend:
Why q8 on Apple Silicon instead of CoreML/Metal?
CoreML compiles Metal shaders on first use (~20 min cold-start). For the typical chunk sizes produced by this server (6–20 chunks per page), the CPU↔GPU transfer overhead eliminates any inference gain. INT8 quantized inference on ARM NEON SIMD is consistently ~100× faster than fp32 CPU with zero cold-start cost.
Benchmark (Apple M-chip, Xenova/nomic-embed-text-v1):
fp32 CPU (before): ~1,000 ms/chunk (68 chunks ≈ 68 s of embedding)
q8 ARM NEON: ~9 ms/chunk (68 chunks ≈ 0.6 s of embedding) ← ~100× speedup
Note: For small crawls (≤ 10 pages) total wall-clock time is dominated by network I/O (HTTPS fetches to docs sites), so the end-to-end improvement is modest. The embedding speedup becomes significant at scale - crawling 500+ pages where embedding previously accounted for hours of runtime. For best crawl performance, run Ollama (
ollama serve) which parallelises inference natively and has no per-chunk overhead.
# Run a one-off re-index (checks hashes, skips unchanged pages)
npm run reindex
# Or from the project directory using node-cron (runs daily at 2 AM)
DATABASE_URL=... node -e "
const { ReindexJob } = require('./dist/jobs/reindexDocs');
const job = new ReindexJob();
job.initialize().then(() => job.scheduleDaily());
"
src/
config/ env.ts · constants.ts
vectorstore/ pgvector.ts · schema.sql
ingestion/ crawler.ts · parser.ts · githubFetcher.ts · markdownParser.ts · chunker.ts · embedder.ts
server/ mcpServer.ts · toolRegistry.ts
jobs/ reindexDocs.ts
index.ts
scripts/
crawl.ts CLI ingestion pipeline
migrate.ts Dynamic schema migration
config-examples/ claude_desktop.json · claude_code.sh · cursor_mcp.json · vscode_mcp.json
docker-compose.yml
.env.example
# Type-check
npx tsc --noEmit
# Run crawl with tsx (no build needed)
npm run crawl -- --product ballerina --limit 5
# Run server in dev mode
npm run dev
Semantic search over WSO2 docs (APIM, IS, MI, Choreo, Ballerina) via RAG and pgvector.
{ "mcpServers": { "io.github.iamvirul-wso2-docs-mcp-server": { "command": "npx", "args": [ "-y", "[email protected]" ], "env": { "DATABASE_URL": "<value>", "EMBEDDING_PROVIDER": "<value>", "OPENAI_API_KEY": "<secret>", "GEMINI_API_KEY": "<secret>", "VOYAGE_API_KEY": "<secret>" } } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ผู้เผยแพร่ระบุตัวแปรสภาพแวดล้อมเหล่านี้: DATABASE_URL, EMBEDDING_PROVIDER, OPENAI_API_KEY, GEMINI_API_KEY, VOYAGE_API_KEY
Wso2 Docs ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-15 Semantic search over WSO2 docs (APIM, IS, MI, Choreo, Ballerina) via RAG and pgvector.