Elasticsearch
This MCP server provides direct integration with Elasticsearch clusters, enabling AI assistants to search indices, retrieve mappings, and list available indices through natural language interactions. Built with FastMCP and the official Elasticsearch Python client, it offers three core tools: search_index for query string searches, list_indices for discovering available data sources, and get_index_mappings for understanding data structure. The implementation includes a demonstration client using LangChain and Ollama's DeepSeek model, with example penalty kick data from CSV files, making it valuable for organizations that need AI-powered access to their Elasticsearch data warehouses, log analysis systems, or search infrastructure without requiring users to learn Elasticsearch query syntax.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/akhilvis/elastic-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Elasticsearch from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp --scope user for --scope project to commit it to .mcp.json.