"A server for monitoring browser console, network, and app logs" matching MCP servers:

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Downloads your entire Search Console dataset into a local SQLite database, then gives your LLM a pre-built SQL query library for every standard SEO analysis type, with context available for your LLM to perform any SQL query to answer your questions and analyse for you.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

An MCP server for internal data platforms that enables search, viewing, tracing, and read-only querying of business assets like dashboards, metrics, and events.

Agent-First CRUD store MCP server — schema.yaml driven, SQLite backend, multi-table in a single daemon.

Enables AI tools to introspect and query any Rails application's models, schema, associations, and data through read-only, token-efficient MCP tools with configurable limits and production safeguards.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables querying daily Oura Ring metrics from a self-hosted Postgres warehouse and rendering interactive trend charts inline in compatible MCP hosts, with text summaries for hosts that lack chart support.

A Model Context Protocol (MCP) server that enables AI assistants to interact with MySQL databases by executing SQL queries and checking database connectivity.

Read-only MCP server for Elasticsearch log querying. Enables natural language search, filtering, context retrieval, and aggregation of logs.

Deploys the Databricks AI Dev Kit MCP server as a Databricks App, exposing over 80 tools for interacting with workspace services like SQL warehouses, Unity Catalog, and AI/BI dashboards. It enables users to manage and query Databricks resources via natural language in the AI Playground using a Streamable HTTP transport.

Enables querying OpenTelemetry logs stored in OpenSearch across development and production environments. Provides tools for searching logs by various criteria including free-text Lucene queries, trace IDs, service names, error levels, and specific fields.

A TypeScript-based MCP server that enables interaction with Azure Table Storage directly through Cline. This tool allows you to query and manage data in Azure Storage Tables.

Enables AI assistants to manage Backendless applications, including databases, users, files, and API services, through natural language commands, with support for OAuth2 authentication and hosted endpoints.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

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.

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.

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.

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

Enables LLMs to interact with generated CRUD services through MCP tools and resources, so they can create, update, list, and fetch records via a standard protocol. It also provides REST API access from the same codebase for traditional clients.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables monitoring and querying of telecom performance management (PM) counters from remote SFTP locations, providing access to interface statistics, CPU/memory utilization, BGP peer data, and system metrics through a conversational interface.

Enables database interaction for a Next.js application using Prisma, supporting queries and mutations through natural language.

Captures and stores console output from any process in SQLite with full-text search, enabling AI assistants to search logs, monitor errors, and analyze multi-process activity through natural language queries.

Enables LLMs to discover and invoke CRUD operations and read-only data resources for generated services through the Model Context Protocol, alongside traditional REST endpoints.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

A read-only MCP server that lets AI clients investigate logs stored in VictoriaLogs over stdio, offering LogsQL search, UUID/stream lookups, stream and field discovery, hit aggregation, and stats queries with time-range and filtering controls. It supports bearer, basic, or anonymous auth, multi-tenant account/project IDs, and response size and timeout limits.

Enables AI assistants to query, search, and analyze LinkedIn profiles from the Headstarter network for recruiting, networking, and community building.

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