"Elastic" matching MCP servers:

This MCP server enables classification of personal inbox messages by actionability, effort duration, and urgency, producing prioritized queues and elastic recommendations that help prevent attention fragmentation.

Enables users and autonomous agents to calculate dynamic price elasticity of demand and identify marginal revenue maxima through a zero-dependency, MCP-compatible Python tool.

Unifies 7,283+ detection rules from Sigma, Splunk ESCU, Elastic, and KQL into a single queryable interface via MCP, with a web dashboard and autonomous agent pipeline for detection engineering.

Sigma detection rule writing, validation, and pySigma-based multi-backend conversion (Splunk, Elastic, Wazuh, Kibana) via 3 MCP tools and 3 Claude Code skills, backed by a 61-rule production corpus across 11 MITRE ATT\&CK tactic categories.

Facilitates interaction with Elasticsearch clusters by allowing users to perform index operations, document searches, and cluster management via a Model Context Protocol server and natural language commands.

Enables personal agents to track habits and receive adaptive micro-fallbacks that degrade gracefully when a streak is missed, rather than letting the user abandon it. Surfaces prioritized queues and elastic recommendations through MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.