Elasticsearch
This Elasticsearch MCP server enables AI models to interact with Elasticsearch clusters, providing tools for managing indices and executing queries. Developed as an open-source project, it integrates with the @elastic/elasticsearch library to offer functionalities like searching, creating indices, listing indices, and indexing documents. The server is built with TypeScript and leverages the @modelcontextprotocol/sdk for MCP implementation. By abstracting Elasticsearch operations, it allows AI systems to easily incorporate powerful search and analytics capabilities into their workflows. This implementation is particularly useful for developers and data scientists working with large datasets, enabling use cases like intelligent data retrieval, automated index management, and AI-driven data analysis in Elasticsearch environments.
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
- data-analytics
- Source
- PulseMCP
- Repository
- github.com/da1y/mcp-server-elasticsearch
- 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.