"Redis MCP server or integration" matching MCP servers:

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.

The official Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis.

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

Overcomes Claude Code's 200k token context limit by implementing persistent long-term memory using Redis and AI-powered state summarization. Enables seamless checkpoint and resume of project context across sessions.

Persistent memory for AI agents through the Model Context Protocol. MemStack provides tools to store, retrieve, summarize, prune, export, and manage memories using local files, SQLite, Postgres, Redis, or in-memory storage.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Provides access to 21+ AI search parsers including Perplexity, ChatGPT, Claude, Gemini, Copilot, Grok, DeepSeek, and traditional search engines through the Redis API, enabling multi-source AI-powered search and information retrieval.

This read-only MCP Server allows you to connect to Redis data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

A proof of concept MCP server for Apache OFBiz

The Wanaku MCP Router stands between autonomous AI agents and your enterprise systems. Wanaku leverages proven integration technology, like Apache Camel, to set up and manage hundreds or thousands of integrations.

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.

Enables Claude and other AI agents to persistently store and retrieve decisions, patterns, and knowledge across sessions, surviving context limits, restarts, and compaction. It supports self-hosted Redis/Valkey or managed cloud deployment with workspace organization and automatic semantic retrieval.

Provides persistent cross-session memory for Claude and other AI agents, so decisions, patterns, and knowledge stored once are automatically retrieved in future conversations. Survives context limits, session restarts, and compaction, with memories organized per workspace and self-hostable on Redis or Valkey.

he Maximo MCP Server bridges AI agents (Claude, Cursor, Antigravity) with your IBM Maximo environment. It empowers your AI to autonomously discover Object Structures (APIs), inspect schemas, and query live data via OSLC. Instead of hallucinating field names, the AI validates queries instantly and ca

Enables Claude and other AI agents to persistently store and retrieve decisions, patterns, and knowledge across sessions, surviving context limits, restarts, and compaction. It supports self-hosting on Redis/Valkey or a managed SaaS setup.

Enables persistent cross-session memory for Claude and other AI agents by storing and automatically retrieving decisions, patterns, and knowledge across conversations, surviving context limits, restarts, and compaction. Supports self-hosting on Redis/Valkey or a managed cloud service.

Provides persistent cross-session memory for Claude and other AI agents by storing and automatically retrieving decisions, patterns, and knowledge across conversations and workspaces. It supports self-hosted Redis/Valkey or managed cloud deployments, helping preserve context beyond session restarts and context limits.

Enables persistent cross-session memory for Claude and other AI agents by storing and automatically retrieving decisions, patterns, and knowledge across sessions. Supports self-hosted Redis/Valkey storage or a managed cloud service.

Enables Claude and other AI agents to store and retrieve persistent cross-session memories, so decisions, patterns, and knowledge survive context limits, restarts, and compaction. Supports self-hosted Redis/Valkey or managed cloud deployment with workspace organization and semantic search.

Provides MCP agents with persistent memory operations (store, recall, forget, consolidate, list) backed by Redis, Postgres, and pgvector, including semantic search and background consolidation.

Gives Claude and other AI agents persistent cross-session memory by storing decisions, coding patterns, and knowledge in a Redis/Valkey instance or a managed cloud backend, then retrieving relevant context automatically. Memories survive session restarts and context compaction, and are organized per workspace so different projects stay isolated.

A FastMCP-based MCP server for the R2R API, enabling integration with document management, knowledge graphs, and RAG systems through automatically generated tools and resources.

Provides read-only MCP tools for AI agents and coding assistants to search podcast transcripts and episode metadata, retrieve transcript excerpts, and generate citations. It requires no login or API key.

Enables AI assistants to query and analyze databases using natural language through MCP and HTTP API, supporting 17+ databases and integration with 50+ platforms.

Enables seamless integration with Weaviate vector databases, providing tools for semantic, keyword, and hybrid search across local or cloud instances. It supports schema management, collection retrieval, and multi-tenancy configurations through the Model Context Protocol.

Enables Claude and other AI agents to store and retrieve decisions, patterns, and knowledge persistently across sessions and context compaction, either self-hosted on Redis/Valkey or through a managed SaaS.

Routes requests to multiple downstream Model Context Protocol servers and provides a LangGraph.js-based agent with RAG capabilities for development assistance.

Enables Claude and other AI agents to store decisions, patterns, and knowledge in persistent cross-session memory that survives restarts and context compaction, then retrieve relevant context automatically in future conversations. Supports self-hosting on Redis or Valkey, or a managed cloud service, with workspace organization, team sharing, and configurable embedding providers.

Gives Claude and other AI agents persistent cross-session memory, so stored decisions, code patterns, and knowledge are automatically retrieved in future conversations and survive restarts and context compaction. It can be run self-hosted on your own Redis or Valkey instance or used as a managed cloud service.

MCP server for NodeBB forums that enables AI assistants to access forum data, search topics, and perform semantic search via the Model Context Protocol.

Enables MCP clients to connect to LLM/API services using the Model Context Protocol, providing real-time interaction and tool access. Also offers RESTful API endpoints via FastAPI for programmatic integration with existing systems.

Serves an AI coding agent a searchable index of a codebase's existing capabilities and past incidents, so it can find and reuse what already exists before writing new code. Also exposes blast-radius analysis for shared code and lets the agent reindex the knowledge base, all via local retrieval with no model calls or API keys.

Intelligent multi-model orchestrator with dynamic routing that optimizes AI costs by prioritizing free models and escalating to paid tiers only when needed, with stateless architecture using Redis and PostgreSQL.

Enables Claude and other AI agents to retain and retrieve decisions, patterns, and knowledge across sessions, surviving context limits, restarts, and compaction. It supports self-hosted Redis/Valkey or managed SaaS, with workspace-scoped memories and semantic search.

Provides semantic search capabilities over PyTorch documentation, enabling users to find relevant documentation, APIs, code examples, and error messages through Claude Code integration.

A production-ready MCP server for persistent AI memory across LLMs like Claude and ChatGPT. Provides automatic conversation backup, multi-user support, and multi-storage (PostgreSQL, Redis, Qdrant).

Provides persistent cross-session memory for Claude and other AI agents, letting users store decisions, code patterns, and knowledge once and have relevant context retrieved automatically in future conversations. Memories survive context limits, restarts, and compaction, and can be organized by workspace or shared across a team when self-hosted on Redis/Valkey or used via the managed cloud service.

Pinecone integration with vector search capabilities