opensearch-skills

name	opensearch-skills
description	Build search applications and query log analytics data with OpenSearch. Use this skill when the user mentions OpenSearch, search app, index setup, search architecture, semantic search, vector search, hybrid search, BM25, dense vector, sparse vector, agentic search, RAG, embeddings, KNN, PDF ingestion, document processing, or any related search topic. Also use for log analytics and observability — when the user wants to set up log ingestion, query logs with PPL, analyze error patterns, set up index lifecycle policies, investigate traces, or check stack health. Activate even if the user says log analysis, Fluent Bit, Fluentd, Logstash, syslog, traceId, OpenTelemetry, or log analytics without mentioning OpenSearch.
compatibility	Requires Docker and uv. AWS deployment requires AWS credentials.
metadata	{"author":"opensearch-project","version":"2.0"}

OpenSearch Skills

This is the top-level skill for OpenSearch. It contains three category skills that can also be installed and used independently:

Category	Skill	Install individually
search	opensearch-launchpad	npx skills add opensearch-project/opensearch-agent-skills@opensearch-launchpad --full-depth
observability	log-analytics	npx skills add opensearch-project/opensearch-agent-skills@log-analytics --full-depth
observability	trace-analytics	npx skills add opensearch-project/opensearch-agent-skills@trace-analytics --full-depth
cloud	aws-setup	npx skills add opensearch-project/opensearch-agent-skills@aws-setup --full-depth

Routing

Route to the right skill based on user intent:

User Intent	Skill
Build a search app, set up an index, choose a search strategy	opensearch-launchpad
Analyze logs, query with PPL, discover error patterns	log-analytics
Investigate traces, debug spans, analyze service maps	trace-analytics
Deploy to AWS, provision a domain or collection	aws-setup
General OpenSearch question	Search docs first, then route to the relevant skill

If the user's intent spans multiple skills (e.g., "build a search app and deploy it to AWS"), start with the appropriate skill and transition to the next when ready.

Shared Resources

All skills share these resources:

• Scripts: scripts/opensearch_ops.py — CLI for all OpenSearch operations
• Docker bootstrap: scripts/start_opensearch.sh — Start a local OpenSearch cluster
• CLI Reference: cli-reference.md — Full command reference with examples
• Search Builder UI: scripts/ui/ — React frontend served on port 8765

bash scripts/start_opensearch.sh
uv run python scripts/opensearch_ops.py <command> [options]
uv run python scripts/opensearch_ops.py --help

Optional MCP Servers

{
  "mcpServers": {
    "ddg-search": {
      "command": "uvx",
      "args": ["duckduckgo-mcp-server"]
    },
    "awslabs.aws-api-mcp-server": {
      "command": "uvx",
      "args": ["awslabs.aws-api-mcp-server@latest"],
      "env": { "FASTMCP_LOG_LEVEL": "ERROR" }
    },
    "aws-knowledge-mcp-server": {
      "command": "uvx",
      "args": ["fastmcp", "run", "https://knowledge-mcp.global.api.aws"],
      "env": { "FASTMCP_LOG_LEVEL": "ERROR" }
    },
    "opensearch-mcp-server": {
      "command": "uvx",
      "args": ["opensearch-mcp-server-py@latest"],
      "env": { "FASTMCP_LOG_LEVEL": "ERROR" }
    }
  }
}

Auto-Installing Missing MCP Servers

Before using any MCP tool, check if the server is available. If missing:

1. Locate the MCP config file:
   • Kiro: .kiro/settings/mcp.json
   • Cursor: .cursor/mcp.json
   • Claude Code: .mcp.json
   • VS Code (Copilot): .vscode/mcp.json
   • Windsurf: ~/.codeium/windsurf/mcp_config.json
2. Read the existing config (or start with {"mcpServers": {}}).
3. Merge in the missing server entry. Do not overwrite existing entries.
4. Save and inform the user to restart or reconnect MCP servers.

Answering OpenSearch Knowledge Questions

uv run python scripts/opensearch_ops.py search-docs --query "<your query>"
uv run python scripts/opensearch_ops.py search-docs --query "<query>" --site docs.aws.amazon.com