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Prajwalnayak7_mcp Server Redis: Unmatched Performance & Scalability - MCP Implementation

Prajwalnayak7_mcp Server Redis: Unmatched Performance & Scalability

Prajwalnayak7_mcp Server Redis: Mirror unmatched Redis performance, scalability, and reliability. Built for real-time enterprise workloads with lightning-fast in-memory mastery." )

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About Prajwalnayak7_mcp Server Redis

What is Prajwalnayak7_mcp Server Redis: Unmatched Performance & Scalability?

This server is a purpose-built Redis integration framework designed for high-performance data operations and seamless scalability. Built on UV's dependency management, it provides a modular architecture with dedicated resource handlers and toolkits for every Redis operation category—from basic key-value storage to advanced pub/sub messaging. The structure is rigorously tested and optimized for production environments, ensuring reliable connections even under heavy loads.

How to use Prajwalnayak7_mcp Server Redis: Unmatched Performance & Scalability?

  1. Set up your environment: uv venv && source .venv/bin/activate
  2. Sync dependencies via uv sync
  3. Configure Redis in .env using UV's guidelines
  4. Launch the server: python src/server.py

Test immediately with mcp dev or deploy via mcp install for Claude Desktop integration.

Prajwalnayak7_mcp Server Redis Features

Key Features of Prajwalnayak7_mcp Server Redis: Unmatched Performance & Scalability?

  • Autonomous reconnection: Automatically resumes Redis links after network interruptions
  • Type-specific toolkits: Separate modules for lists, hashes, sets, and pub/sub operations
  • Pattern-based querying: Fetch keys matching custom patterns via redis://keys/{pattern}
  • LLM-friendly responses: Human-readable outputs with structured error handling

Every operation includes detailed status codes and contextual messages, making debugging a breeze.

Use cases of Prajwalnayak7_mcp Server Redis: Unmatched Performance & Scalability?

Power real-time applications like:

  • User sessions: Store and invalidate auth tokens with set_value expiry
  • Message queues: Scale pub/sub listeners for chat apps using pubsub.py
  • Leaderboards: Maintain sorted rankings via set operations
  • Cache invalidation: Use pattern-based key deletion for stale data cleanup

One-click testing with mcp dev ensures your workflows are battle-tested before deployment.

Prajwalnayak7_mcp Server Redis FAQ

FAQ from Prajwalnayak7_mcp Server Redis: Unmatched Performance & Scalability?

  • Does it support Redis clusters? Yes, configure REDIS_CLUSTER_MODE=true in .env
  • How to add custom commands? Extend tools/ with new .py files adhering to the interface
  • Error: "Connection refused" Check Redis service status and firewall rules
  • Can I use this with Docker? Yes, modify pyproject.toml to include your Redis container

For advanced scenarios, refer to the UV docs for environment variable overrides.

Content

Usage

The structure is as follows:

mcp-server-redis/
├── src/
│   ├── __init__.py
│   ├── main.py           # Main entry point
│   ├── config.py         # Configuration
│   ├── connection.py     # Redis connection management
│   ├── resources/        # Resource implementations
│   │   ├── __init__.py
│   │   ├── status.py     # Connection status resources
│   │   └── keys.py       # Key-related resources
│   └── tools/           # Tool implementations
│       ├── __init__.py
│       ├── basic.py     # Basic Redis operations
│       ├── lists.py     # List operations
│       ├── hashes.py    # Hash operations
│       ├── sets.py      # Set operations
│       └── pubsub.py    # Pub/Sub operations
├── tests/              # Test directory
│   └── __init__.py
├── README.md
└── pyproject.toml

To use this server, you'll need to:

Install the required dependencies:

[If not already installed] https://docs.astral.sh/uv/

uv venv

source .venv/bin/activate

uv sync

Refer to the .env.example file to configure your Redis connection by adding the appropriate variables.

Run the server:

python src/server.py

Capabilities of this server

Resources:

  • redis://status - Current connection status
  • redis://info - Redis server information
  • redis://keys/{pattern} - List keys matching a pattern

Tools:

  • Basic operations:
    • get_value - Get a value
    • set_value - Set a value with optional expiry
    • delete_key - Delete a key
    • increment - Increment a numeric value
  • List operations:
    • list_push - Push values to a list
    • list_range - Get range of list values
  • Hash operations:
    • hash_set - Set hash fields
    • hash_get - Get hash fields
  • Set operations:
    • set_add - Add to a set
    • set_members - Get set members
  • Pub/Sub:
    • publish_message - Publish a message

Each tool includes error handling and returns meaningful responses. The server will automatically reconnect to Redis if the connection is lost.

You can test it with the MCP Inspector: mcp dev src/server.py

Or install it in Claude Desktop: mcp install src/server.py

Example

User: What's the current Redis connection status?
LLM: Let me check the Redis connection status for you.

[Reading resource redis://status]

The Redis server is currently connected and running on localhost:6379, database 0.

User: Can you store my name "Alice" in Redis?
LLM: I'll help you store your name in Redis using the set_value tool.

[Calling set_value with key="name" value="Alice"]
Successfully set key 'name'

I've stored your name "Alice" in Redis under the key "name". Would you like me to verify the value was stored correctly by retrieving it?

User: Yes please verify it
LLM: I'll retrieve the value using the get_value tool.

[Calling get_value with key="name"]
Alice

Yes, I can confirm that your name "Alice" was successfully stored in Redis and can be retrieved correctly. The value matches exactly what we stored.

This implementation provides a solid foundation for Redis integration through MCP. You can extend it further by adding more Redis commands as needed for your specific use case.

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