"How to view console logs in a development environment" matching MCP servers:

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

Enables AI assistants to search live jobs, view full details, save and track applications in a Kanban board, set follow-up reminders, and subscribe to job alerts—no account needed for searching.

Track how your brand appears in AI-generated answers across ChatGPT, Perplexity, and other AI models. Analyze visibility, sentiment, citations, and domain rankings with 31 tools — including analytics reports, chat inspection, query analysis, and full CRUD for brands, prompts, tags, and topics.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.

Enables AI assistants to search and view public tenders from Switzerland's simap.ch platform.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

A local bridge that lets MCP clients inspect, export, and modify Figma files through a development Figma plugin.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

Integrates front-end development servers with AI tools, enabling browser automation, console log capture, screenshot management, and HMR event monitoring.

A Model Context Protocol server that connects to Google Cloud services, allowing users to query logs, interact with Spanner databases, and analyze Cloud Monitoring metrics through natural language interaction.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

Provides unofficial access to Philippine Stock Exchange data including quotes, price history, disclosures, financial reports, and market data via MCP.