"Upstash" matching MCP servers:

Model Context Protocol (MCP) is a new, standardized protocol for managing context between large language models (LLMs) and external systems. In this repository, we provide an installer as well as an MCP Server for Upstash Developer API's.

Lightweight MCP server for Redis that allows running any Redis command and searching Redis documentation. Supports multiple named databases with HTTP/REST or TCP transport.

A FastMCP server that enables AI agents to schedule notifications and reminders via Upstash QStash and NTFY.

A Model Context Protocol server that fetches up-to-date, version-specific documentation and code examples from libraries directly into LLM prompts, helping developers get accurate answers without outdated or hallucinated information.

Provides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.

An MCP server that enables users to query any Mintlify-powered documentation site directly from Claude. It leverages Mintlify's AI Assistant API to provide RAG-based answers and code examples for various platforms like Agno, Resend, and Upstash.

Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.

Enables read-only access to NORA dashboard data from Upstash Redis, covering OKRs, initiatives, KPIs, and financial summaries. It allows users to query and analyze business performance metrics and organizational alignment through standardized MCP tools.

Enables semantic search and ingestion of investor content using Upstash Vector and Vercel Blob storage, with optional filtering by author, company, and date.