"Analyzing Python Modules, Docker Files, and Generating Mock Data or Outputs" matching MCP servers:

Spin up deterministic mock MCP servers from JSON fixture files for testing MCP clients and agents.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Enables Claude Cowork on Windows to read, write, edit, list, find, and regex-search files inside a WSL distribution over stdio, accepting Windows and Linux path spellings. Access is confined to server-fixed roots, with secrets files refused, key-shaped strings redacted, and no delete or move operations.

Generates schema-compliant mock data from OpenAPI JSON Schema definitions using AI, enabling seamless testing without manual fixtures.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

A minimal local HTTP MCP mock server for development and testing, providing predictable tool responses with OAuth token support and zero dependencies.

Enables AI clients to interact with a mock JIRA-shaped issue tracker through MCP tools for managing projects, issues, and users.

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

A local stdio MCP server for managing files on XServer via SFTP, enabling secure file operations, backups, and workspace management for XServer hosting.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

Enables an AI agent to run and inspect containers, build and pull images, manage volumes and networks, drive Compose projects, clean up, and run self-checking practice labs. Startup modes restrict it to read-only, labs-only, or full Docker control with confirmation before dangerous operations.

A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.

A powerful Model Context Protocol (MCP) server for Docker operations, enabling seamless container and compose stack management through Claude AI.

A mock MCP server for testing MCP client implementations and development workflows. Supports tools, prompts, and resources across multiple transport protocols (stdio, HTTP, SSE).

A zero-dependency mock MCP server for testing MCP clients and harnesses, with configurable tools and canned responses.

This TypeScript-based MCP server implements a simple notes system, allowing the creation, listing, and summarization of text notes using MCP concepts with note:// URIs and metadata.

MCP server to mock OpenAI, Anthropic, and Google Gemini responses for testing AI integrations without real API keys or token spend.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

Enables ChatGPT/Codex to read, search, and edit files in a single allowed folder on Windows through OpenAI Secure MCP Tunnel.

Enables read-only inspection and narrowly scoped maintenance of a local Docker Desktop environment, covering containers, images, logs, stats, Compose status, and Scout vulnerability/SBOM data, plus limited actions such as image pulls, container restarts, dangling-image pruning, and allowlisted Compose redeploys, all without exposing the raw Docker socket to the client.

A Model Context Protocol server that provides tools for interacting with Docker images, containers, and registries, enabling AI assistants to search, analyze, and manage Docker resources through a standardized interface.

Stdio MCP server for sandboxed file access — read files, search content, safely edit with checksums, and manage file structure.

Enables inspecting, orchestrating, and troubleshooting Docker Engine and Docker Compose environments through six consolidated high-leverage MCP tools.

Enables interaction with Docker containers and images via tools and resources.

Provides Docker container creation and image pulling via the Docker Engine API, with safety guardrails against privileged operations and network exposure.

Enables AI agents to search and query the public DOJ Epstein Files release across 20 databases, resolve EFTA numbers to official DOJ PDFs, and cross-check viral claims against a fact-checked registry.

Enables instant creation of mock API servers from OpenAPI specs or natural language descriptions, with built-in fake data generation, CRUD endpoints, and configurable delays/errors for testing.

Enables developers to run spec-driven, deterministic mock tool interactions for agent integration testing and CI, including fixture-based JSON-RPC responses, call assertions, and error injection without live backends or network access.

Enables AI agents to safely explore directories, read files, search content by pattern or filename, and edit files with checksum verification and dry-run preview within sandboxed filesystem access.

A tool that helps AI agents interact with Docker containers on local or remote machines, allowing users to manage and troubleshoot containers without Docker knowledge.