Redis MCP Server

Overview

• "Store the entire conversation in a stream"

• "Cache this item"

• "Store the session with an expiration time"

• "Index and search this vector"

Features

• Natural Language Queries: Enables AI agents to query and update Redis using natural language.

• Seamless MCP Integration: Works with any MCP client for smooth communication.

• Full Redis Support: Handles hashes, lists, sets, sorted sets, streams, and more.

• Search & Filtering: Supports efficient data retrieval and searching in Redis.

• Scalable & Lightweight: Designed for high-performance data operations.

Tools

• string tools to set, get strings with expiration. Useful for storing simple configuration values, session data, or caching responses.

• hash tools to store field-value pairs within a single key. The hash can store vector embeddings. Useful for representing objects with multiple attributes, user profiles, or product information where fields can be accessed individually.

• list tools with common operations to append and pop items. Useful for queues, message brokers, or maintaining a list of most recent actions.

• set tools to add, remove and list set members. Useful for tracking unique values like user IDs or tags, and for performing set operations like intersection.

• sorted set tools to manage data for e.g. leaderboards, priority queues, or time-based analytics with score-based ordering.

• pub/sub functionality to publish messages to channels and subscribe to receive them. Useful for real-time notifications, chat applications, or distributing updates to multiple clients.

• streams tools to add, read, and delete from data streams. Useful for event sourcing, activity feeds, or sensor data logging with consumer groups support.

• JSON tools to store, retrieve, and manipulate JSON documents in Redis. Useful for complex nested data structures, document databases, or configuration management with path-based access.

• query engine tools to manage vector indexes and perform vector search

• server management tool to retrieve information about the database

Installation

Installing via Smithery

Manual Installation

Configuration

Integration with OpenAI Agents SDK

Integration with Claude Desktop

1. Specify your Redis credentials and TLS configuration

2. Retrieve your uv command full path (e.g. which uv)

3. Edit the claude_desktop_config.json configuration file

Testing

Example Use Cases

• AI Assistants: Enable LLMs to fetch, store, and process data in Redis.

• Chatbots & Virtual Agents: Retrieve session data, manage queues, and personalize responses.

• Data Search & Analytics: Query Redis for real-time insights and fast lookups.

• Event Processing: Manage event streams with Redis Streams.

Contributing

1. Fork the repo

2. Create a new branch (feature-branch)

3. Commit your changes

4. Push to your branch and submit a PR!

License

Contact

Redis MCP Server

Overview

• "Store the entire conversation in a stream"

• "Cache this item"

• "Store the session with an expiration time"

• "Index and search this vector"

Features

• Natural Language Queries: Enables AI agents to query and update Redis using natural language.

• Seamless MCP Integration: Works with any MCP client for smooth communication.

• Full Redis Support: Handles hashes, lists, sets, sorted sets, streams, and more.

• Search & Filtering: Supports efficient data retrieval and searching in Redis.

• Scalable & Lightweight: Designed for high-performance data operations.

Tools

• string tools to set, get strings with expiration. Useful for storing simple configuration values, session data, or caching responses.

• hash tools to store field-value pairs within a single key. The hash can store vector embeddings. Useful for representing objects with multiple attributes, user profiles, or product information where fields can be accessed individually.

• list tools with common operations to append and pop items. Useful for queues, message brokers, or maintaining a list of most recent actions.

• set tools to add, remove and list set members. Useful for tracking unique values like user IDs or tags, and for performing set operations like intersection.

• sorted set tools to manage data for e.g. leaderboards, priority queues, or time-based analytics with score-based ordering.

• pub/sub functionality to publish messages to channels and subscribe to receive them. Useful for real-time notifications, chat applications, or distributing updates to multiple clients.

• streams tools to add, read, and delete from data streams. Useful for event sourcing, activity feeds, or sensor data logging with consumer groups support.

• JSON tools to store, retrieve, and manipulate JSON documents in Redis. Useful for complex nested data structures, document databases, or configuration management with path-based access.

• query engine tools to manage vector indexes and perform vector search

• server management tool to retrieve information about the database

Installation

Installing via Smithery

Manual Installation

Configuration

Integration with OpenAI Agents SDK

Integration with Claude Desktop

1. Specify your Redis credentials and TLS configuration

2. Retrieve your uv command full path (e.g. which uv)

3. Edit the claude_desktop_config.json configuration file

Testing

Example Use Cases

• AI Assistants: Enable LLMs to fetch, store, and process data in Redis.

• Chatbots & Virtual Agents: Retrieve session data, manage queues, and personalize responses.

• Data Search & Analytics: Query Redis for real-time insights and fast lookups.

• Event Processing: Manage event streams with Redis Streams.

Contributing

1. Fork the repo

2. Create a new branch (feature-branch)

3. Commit your changes

4. Push to your branch and submit a PR!

License

Contact