"Collecting and Analyzing Server-Side Errors Based on MySQL, Redis, and Elasticsearch" matching MCP servers:

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Provides access to Redis databases. This server enables LLMs to interact with Redis key-value stores through a set of standardized tools.

Bridges Xcode and Cursor to provide real-time access to build errors, warnings, and debug output from Xcode's DerivedData, enabling automated error analysis and fixes directly within Cursor.

Read/write Elasticsearch mcp server with many tools

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Connects agents to Elasticsearch data using the Model Context Protocol, allowing natural language interaction with Elasticsearch indices through MCP Clients like Claude Desktop and Cursor.

This is an elasticsearch mcp server developed based on sprint ai.

A safe, connection-efficient Redis MCP server that provides tools for reading and managing Redis data, with safeguards like confirmation requirements for destructive operations.

An MCP Server that provides a conversational interface to the UK Open Banking account information API, allowing agents to interact with bank account data through natural language commands.

A Model Context Protocol (MCP) server for interacting with MySQL databases. Provides tools for querying, inspecting, and modifying databases directly from Claude.

A Model Context Protocol (MCP) server for Redis. Connect to any Redis instance and execute queries through AI assistants.

Enables LLMs to safely explore and operate Redis instances, with read-only keyspace inspection, multi-structure data access, memory and big-key analysis, slow query diagnostics, and optional opt-in write operations.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

MCP server that exposes Redis API to AI models

Enables users to perform Redis database operations using the Model Context Protocol (MCP) tools, allowing for efficient data management through commands like setting, getting, and scanning hash fields.

MCP server for Redis with data operations, permission control, and operation logging. Supports key management, dynamic tool lists, and auto-reconnection.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

Enables LLMs and MCP clients to discover and use generated CRUD services through MCP tools and resources, exposing actions like create, update, delete, and read-only list/get access alongside REST endpoints.

Enables AI assistants to discover and invoke generated CRUD tools and read-only resources, letting them interact directly with REST-backed services built on Express, Mongoose, or Sequelize.

Enables LLMs and AI assistants to discover and use tools and resources for CRUD operations on generated services, providing direct interaction with the same data exposed by REST endpoints.

Enables LLMs to discover and invoke CRUD tools and read-only resources for generated services, allowing direct interaction with the same data exposed by the REST API.