"Google BigQuery cloud data warehouse service" matching MCP servers:

Enables LLMs to explore BigQuery datasets and tables, run safe read-only queries, and optionally perform vector search using BigQuery embeddings.

This is a server that lets your LLMs (like Claude) talk directly to your BigQuery data! Think of it as a friendly translator that sits between your AI assistant and your database, making sure they can chat securely and efficiently.

A Model Context Protocol server that provides access to BigQuery. This server enables LLMs to inspect database schemas and execute queries.

Enables secure access to BigQuery datasets with intelligent query result caching, schema evolution tracking, and AI-powered query optimization recommendations through Supabase integration.

A private MCP server that converts natural-language questions into embeddings and performs semantic retrieval over document chunks stored in BigQuery, returning structured passages with source and page metadata. It serves as the read-only retrieval layer for a document-grounded chatbot.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Salesforce Data Cloud (beta): https://www.cdata.com/download/download.aspx?sku=LRZK-V&type=beta

Self-hosted service providing unified memory search and write operations across file-based memory, vector embeddings, and the Graphiti temporal knowledge graph, accessible via HTTP API or MCP stdio transport.

Persistent memory infrastructure for AI systems, running on Cloudflare's edge network with 28 MCP tools for semantic memory, emotional processing, identity continuity, and a subconscious daemon.

A production-minded RAG service for MCP that answers questions over your documents with hybrid retrieval, PII redaction, and source citations, packaged for Docker/Kubernetes.

Provides self-hosted, versioned project memory with full-text and vector search, enabling search, retrieval, upsertion, and history management of project entries via MCP tools.

The Redis Cloud API MCP Server provides an MCP Server for Redis Cloud's API, allowing you to manage your Redis Cloud resources using natural language.

Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.

Provides AI agents and teams with self-hosted adaptive memory, combining hybrid search and a self-improving neural memory graph to enable precise recall and serendipitous discovery across MCP-compatible clients.

Provides hybrid retrieval (dense + BM25 + RRF) with collection-based isolation and document ingestion for private knowledge access via MCP.

This MCP server enables employees to ask IT questions, receive evidence-backed answers, and trigger traceable work orders or escalations through authenticated MCP tools. It also supports status checks, durable action jobs, and auditable work-order, Excel ledger, and escalation workflows.

A cloud MCP server providing Tavily-powered tools for web search, extraction, crawling, mapping, and research, with multi-key load balancing, real-time quota tracking, and a web admin panel.

This MCP server provides semantic document search and retrieval, enabling AI assistants to search documents, search categories, and retrieve category hierarchies using the Model Context Protocol.

Zep Cloud MCP Server: Provides memory management via the Zep Cloud API. Enables storing and retrieving user preferences, procedures, and factual relationships through a knowledge graph. Supports fallback mode for reliable operation when API is unreachable.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Google Data Catalog (beta): https://www.cdata.com/download/download.aspx?sku=HGZK-V&type=beta