"Tools for Testing in Python and Java" matching MCP servers:

Provides tools for frontend testing including code analysis, test generation, test execution, and React component testing for Jest and Cypress frameworks.

A full-stack API automation testing server that parses OpenAPI/Swagger/Postman/HAR specs, generates comprehensive test scenarios and executable code, and provides AI-powered review and auto-fix.

Provides coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

A Model Context Protocol server that provides Azure Java SDK documentation to AI assistants, allowing them to access readme files with introductions, key concepts, and code samples.

Exposes the SiftingIO market-data SDK to AI assistants, enabling live prices, fundamental data, and market information retrieval.

Enables an Alexa+ host to place and manage customer-care calls by building a case, navigating phone menus, waiting on hold, explaining the issue, guarding sensitive disclosures, handing off identity checks, recording ticket numbers and promises, and scheduling follow-ups.

A full-featured secure MCP server for local file system operations, with built-in image processing, OCR and media tools.

Persistent memory and pattern learning for AI coding assistants via MCP.

Enables users to describe an LLM fine-tuning job once and receive VRAM/FLOPs-aware recommendations for the cheapest, fastest, or most balanced GPU options across a dozen cloud providers.

Enables deterministic calculations for AI API and subscription costs, meeting time zones, recurring schedules, and cron next-run previews, returning normalized inputs, units, assumptions, dated sources, and links to results.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

A Model Context Protocol server that brings the capabilities of enigmapython library to LLMs, allowing them to encrypt and decrypt messages using historically accurate Enigma machine emulators

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Serves plain-text notes that an Obsidian user has explicitly published for AI over streamable HTTP, with full-text and embedding-based search. MCP clients can read and search those notes and queue suggested edits that the user's own client applies only if the AI rules allow it.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

Aggregates multiple MCP services into a single unified interface with self-configuration capabilities, enabling dynamic addition and removal of tools via conversation.

A Python template for creating MCP servers with embedded documentation, featuring example weather service tools using the NWS API.

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.

Transforms any API into an intelligent MCP agent in seconds, enabling natural language interaction with APIs through the Model Context Protocol.

A streamlined foundation for building Model Context Protocol servers in Python, designed to make AI-assisted development of MCP tools easier and more efficient.

Enables AI agents to perform common utility tasks through a streamable HTTP MCP endpoint, including JSON inspection, regex testing, cron parsing, hashing, base64 encoding/decoding, URL analysis, color conversion, text diffing, CSV parsing, JWT decode/verification, Markdown-to-HTML rendering, and UUID/token generation without API keys.

Enables users to describe a project in an MCP client and work through pre-submission grant phases, including finding fitting programs, checking eligibility and blockers, pulling precedent from past awards, shortlisting, and drafting memos, budgets, and submission checklists. Coverage is full for US grants and partial (discovery and precedent only) for Canada, with no win-odds estimates or post-award reporting.

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.

An MCP (Model Context Protocol) server implementation using HTTP SSE (Server-Sent Events) connections with built-in utility tools including echo, time, calculator, and weather query functionality.

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

A modular multi-server architecture providing development automation, JIRA management, and performance reporting for Claude Code. It features specialized tools for PR health analysis, code reviews, and generating comprehensive team and individual quarterly reports.

It enables users to describe an LLM fine-tuning workload once and receive task-aware VRAM/FLOPs estimates plus ranked cheapest, fastest, or balanced GPU recommendations across multiple cloud providers.

This template enables developers to quickly scaffold, deploy, and extend a Model Context Protocol server on Render, with bearer-token authentication and a streamable HTTP endpoint, by adding custom tools via Python.

Enables AI agents to run passive, boundary, and gated active reconnaissance and web-security CLI tools (nmap, sqlmap, commix, httpx, ffuf, nikto, subfinder, and more) against authorized targets through a persistent, API-key-protected HTTP service. Scope gates, authorization windows, evidence capture, and a full audit trail are enforced in code so every tool call stays within the engagement's declared rules.

Extends VS Code Copilot with MCP tools for persistent semantic memory, code indexing and RAG search, sandboxed Python/shell execution, web fetch/search, dynamic tool management via a web UI, and structured multi-step reasoning.

Enables users to describe an LLM fine-tuning workload once and receive ranked cloud GPU recommendations with estimated VRAM/FLOPs requirements, cost, runtime, and data-source transparency.

A minimal MCP server template for Python with Streamable HTTP transport, bearer token authentication, and a health check endpoint, designed for one-click deployment on Render.

Enables AI-powered LinkedIn automation, including content generation, profile and company data extraction, connection requests, and post scraping through MCP tools.

A Python implementation of an MCP server for Xiaohongshu that enables AI models to browse feeds, search content, and manage interactions like liking or commenting. It leverages Playwright for browser automation to support account management and content publishing features.

A minimal MCP server template for Python with Streamable HTTP transport, bearer token authentication, and a hello tool, designed for deployment on Render.