"List of Servers Running as Docker Containers" matching MCP servers:

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.

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.

An HTTP/HTTPS MITM proxy server that enables capture, modification, and mocking of network traffic across Chrome, CLI tools, Docker containers, and Android devices. It supports advanced capabilities like JA3/JA4 TLS fingerprinting, JA3 spoofing, and upstream proxy chaining.

Integrates GlitchTip error monitoring with AI assistants to fetch, analyze, and debug production errors. It enables users to list issues, retrieve event details, and perform guided triage of application errors through natural language.

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.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.

Enables AI assistants to generate real images via multiple models (OpenAI, Gemini, Recraft, Seedream, Grok, Arrow) and returns usable file paths instead of base64 data.

Provides AI agents with access to the Colyseus documentation, enabling searching, reading, and listing of documentation pages.

Enables any MCP-compatible LLM to perform AI-powered web research using Google's AI Mode, returning synthesized and cited answers instead of raw search results.

Enables local SOC 2 compliance work by scanning Infrastructure-as-Code, mapping findings to SOC 2 Trust Services Criteria, explaining risks in plain English, and drafting audit-ready documents without uploading files.

Enables Yelp business search, place details, and full review feeds as structured JSON through a hosted MCP endpoint, with no Yelp Fusion key required.

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

Enables MCP clients to search Amazon products, retrieve product details by ASIN, look up seller profiles, and browse seller catalogues as structured JSON across 23 regional Amazon domains.

An MCP server that lets LLM agents operate the IDnow Trust Platform sandbox to list verification flows, create sessions, check sessions, and get session details.

Cite-able, content-addressed, signed memory of every place on Earth

Enables MCP clients to search Walmart products by keyword or category, retrieve product details including the buy box and other sellers, and page through customer reviews with filters, all as structured JSON without a Walmart developer account.

Provides verified ANZ public holidays, school terms, and business-day calculations for all 9 regions of Australia and New Zealand, backed by data for 2026 and 2027.

Local design engine for AI Agents. Create, edit and export real, editable designs — social posts, flyers, print-ready PDFs — with your brand applied. Every design opens in a built-in editor, so you can click the text and fix it yourself instead of re-prompting. Bring in what you already have: InDesign, PSD, PPX and PDF files come in as editable designs. Runs on your machine, no account needed.

Enables MCP clients to search Yellow Pages local businesses by keyword and location and retrieve full listing details such as phone, hours, services, brands, and payment methods.

Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.