"An overview of Docker and related information" matching MCP servers:

An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

Gives any MCP client the same sandboxed coding-agent toolset — searching, viewing and editing files, running tests, and executing shell commands — each session in its own locked-down, network-isolated Docker container. Enables an MCP-capable assistant to diagnose and fix failing tests without touching the host machine.

A single, queryable source of engineering constraints that coding agents consult at code-generation time, exposed over an MCP server.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

Runs as an MCP server providing file system operations, shell execution, and system information tools, allowing Claude or any MCP client to edit files and control the machine.

Gives coding agents structural understanding of a codebase: it indexes Java and Python repositories to resolve symbols, call sites with confidence tiers, module dependencies, diff impact, and hotspots. It also ships an eval harness that measures whether this context actually helps an agent.

An MCP server that enables coding agents to run Claude Agent SDK sessions as asynchronous sub-agents, with tools for starting, continuing, and checking status of Claude sessions.

Self-hosted coding agent that runs Claude Code or Codex in your own infrastructure and works from Slack. Exposes codebase investigation, file edits, branch and PR creation, allowlisted command execution, CI status and an audit log as MCP tools, keeping every credential behind the tool layer instead of handing it to the model.

An MCP server for managing, editing, and running Stata .do files, integrating with Claude Desktop to enable natural language control of Stata analysis on macOS.

Unified capability catalogue with formally verified cartridges, distributed community hosting, and the Teranga menu system for single gateway access to a vast rabbfe of MCP, LSP, NeSy and related servers.!

Connects AI assistants to an AgentX account so they can list and inspect a fleet of AI coding agents running on the user's own machines, read their output, send them messages, create chats, wait for events, and retrieve artifacts. Sign-in happens through browser-based OAuth, with no API key or local install required.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

Enables finding existing shadcn-format UI components by plain-language description instead of exact names, returning ranked matches with install commands and per-dimension match reasons.

Enables an authorized MCP agent to discover profiles, read existing Codex sessions and statuses, send or clarify tasks, and stop an exact turn across multiple computers and profiles.

An MCP server for orchestrating a fleet of CLI coding agents in isolated git worktrees. It exposes tools for spawning workers, sending instructions, reviewing diffs, and merging changes, with full terminal visibility.

Enables external AI clients to invoke an autonomous coding agent that plans, fixes, and self-corrects code in an isolated Docker sandbox via run_task and run_tests tools.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

Code-pinned team memory for AI coding agents — typed artifacts (Decision/Analysis/Debug/Task), MCP-native workflow, self-host with Docker Compose.

MCP server that lets Claude, ChatGPT, or VS Code build a complete, machine-checked model of your domain and generate an app from it.

An MCP server that analyzes codebases and generates contextual prompts, making it easier for AI assistants to understand and work with code repositories.

Enables users to run shell commands with compressed output, extract information from large files, drive local opencode and Codex agents, perform browser-automation tasks, and monitor runs via a live dashboard.

Connects AI coding agents to FlutterFlow projects, enabling browsing, inspection, and modification of projects directly from the assistant.

An MCP server that lets any MCP-capable agent spawn and drive Claude Code sessions — effectively turning Claude Code into an orchestratable sub-agent fleet.

Provides AI-powered development assistance with continuous chain-of-thought reasoning (CoConuT), automated task planning and execution, quality validation, and persistent memory of project context and decisions.

A Windows proof-of-concept MCP server that connects ChatGPT developer-mode to a local Codex CLI via Secure MCP Tunnel, exposing a small set of read-only, allowlisted tools in an isolated workspace.

dev-brain-mcp

An MCP server implementing the TRUE Recursive Language Model technique for managing large context windows in Claude Code, enabling analysis of codebases beyond 200k tokens by storing content as variables and using LLM-generated code for search and analysis.

This MCP server enables automated maintenance and code analysis for Python/pytest repositories in isolated Docker environments. It supports read-only investigations, fix-and-verify tasks, and provides full audit trails with SQLite event history and artifact exports.