"Real estate listings in France" matching MCP servers:

. A good description should be concise and describe what the server enables users to do, e.g. * Enables to interact with WordPress sites...' Then a huge block? Actually the user message includes the README content inside tags, then after the readme, there is a large block of text starting with '{

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

Enables offline, real-time search of Apple Developer Documentation from Xcode's local index, returning full text, code examples, availability, and framework listings without network calls.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Enables AI assistants to read and search Hacker News for top stories, comments, user profiles, and job listings using the Firebase and Algolia APIs. It facilitates natural language research into community discussions and technological trends across the HN platform.

MCP server + Chrome extension that gives AI coding agents control of your real browser with existing sessions, logins, and cookies. Works with Cursor, Claude, Windsurf.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables sharing coding progress on Twitter by analyzing sessions and generating tweet suggestions, with tools for posting tweets, threads, and OAuth authentication.

Unifies Roblox Studio, Unity, Unreal Engine, and Blender into a single AI-powered control plane with 78 tools for automated game development.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

This MCP server enables real-time debugging and inspection of running React Native apps, providing access to console logs, errors, network requests, navigation state, storage, and performance profiling.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

Provides JSDelivr CDN statistics and package information for npm packages and GitHub repositories, enabling queries on request counts, bandwidth, file listings, and version resolution.

Local stdio MCP server for Bitwarden (Public API + Secrets Manager). 50+ admin tools for members, groups, collections, policies, licensing, projects, and secrets. For Claude Desktop / Claude Code.

A minimal, dependency-free MCP server demonstrating the 2026-07-28 protocol with a toy example of sending a person to check something in the physical world and returning structured evidence, ideal for learning the protocol layer.

Enables AI assistants to read and improve Google Play store listings for Android apps by fetching localized texts, creating validated local drafts with diffs, and optionally applying approved changes only after explicit confirmation.

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

Enables Garmin Connect IQ developers to inspect store versions, listings, reviews, and installs, run SDK builds and simulator workflows, and optionally access Garmin Connect data through an agent, with read-only defaults and confirmation before public actions.

Provides a safe FastMCP Streamable HTTP server with deterministic mock real-estate tools for testing whether LLMs discover and call only advertised MCP tools.

Enables any MCP client to drive the user's real Chrome profile through a Chrome extension bridge, with tools for navigation, accessibility snapshots, ref-based interactions, console/network reading, screenshots, tab management, and restricted script evaluation.

Enables locally running AI agents to access documents, workflows, memory, chats, code projects, and tool listings through a loopback-only endpoint, with each source opt-in and changes approved in the desktop app.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.

Enables users to describe an LLM fine-tuning job and receive the cheapest, fastest, or most balanced GPU options across multiple cloud providers by calculating required VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job and receive ranked GPU recommendations across a dozen cloud providers based on estimated VRAM/FLOPs, live pricing, cost, and speed. It returns cheapest, fastest, and balanced hardware options without manual comparison.

Enables users to describe an LLM fine-tuning job once and get ranked GPU hardware recommendations with estimated VRAM/FLOPs, cost, and runtime across a dozen cloud providers.

It enables users to describe an LLM fine-tuning workload once and receive ranked GPU recommendations for cheapest, fastest, or balanced options across many cloud providers by estimating VRAM/FLOPs and aggregating live pricing.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...