"Querying Elasticsearch (ES)" matching MCP servers:

Provides persistent, intelligent memory using Elasticsearch with hierarchical categorization and semantic search for LLM contexts.

Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.

An MCP server that provides AI agents with a persistent, PostgreSQL-backed virtual filesystem, supporting session-isolated file operations, cross-session shared stores, and glob/grep search.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

Enables querying, creating, and managing Zotero references via the MCP protocol.

A comprehensive Model Context Protocol server that integrates Elasticsearch search with file operations, document validation, and version control to transform AI assistants into powerful knowledge management systems.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

Dual-memory MCP system with PostgreSQL 17 + pgvector + NVIDIA NIM embeddings. 11 tools: search, save, profile, health, auto-repair, stats, tune, dedup, checkpoint, maintenance. Sparse Selective Caching (SSC) with 4-phase progressive retrieval. Bilingual EN/ES.

Complete knowledge management for AI assistants with Elasticsearch search and document management.

Enables querying and retrieving content from Confluence through CQL searches and page content fetching, allowing Claude to seamlessly access information stored in Confluence workspaces.

Enables seamless integration between Claude and Dry smartspaces, turning conversations into persistent, structured data by creating memories and querying information.

A Python library for storing and querying n-ary relationships with provenance tracking. SQLite-backed, zero configuration.

Enables querying and managing personal/team internal knowledge from sources like Slack, Gmail, and Drive through semantic search and retrieval.

Provides persistent tribal memory for Claude Code sessions, enabling querying of decisions and entities, logging artifacts, and managing tasks with Supabase.

MCP server for querying the DodaOne governance framework, enabling users to retrieve governance information and evaluate proposed actions.

Enables querying, listing, and summarizing personal knowledge base documents using RAG with hybrid search and LLM.

Enables read-only querying of a verified knowledge library through an API and MCP interface, letting people and agents ask questions about systems discovery findings.

Enables source-first orchestration and knowledge indexing with inspectable architectural capabilities through a unified MCP interface, including named-attribute retrieval and atomic knowledge ingestion.

Secure MCP server for querying Google NotebookLM notebooks. Enables AI assistants to list notebooks, read sources, and ask the NotebookLM AI questions about your sources.