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maintenanceFlask Extension for apcore (AI-Perceivable Core) integration. Expose your Flask routes as MCP tools with auto-discovery, Pydantic schema inference, and built-in observability.
Apache 2.0
70,780 servers. Updated
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"Flask" matching MCP servers:
FLASK-toolsofficial
Flicense-qualityBmaintenanceProvides a collection of MCP servers for computational chemistry tasks including molecular generation and retrosynthesis. Also offers property prediction and molecule pricing capabilities.- Alicense-qualityDmaintenanceFlask-based Model Context Protocol (MCP) server for Python. Drop it into any Flask app or run it standalone.7MIT
- Alicense-qualityDmaintenanceFlask-MCP-Plus enables developers to create MCP servers using Flask, with support for defining tools, resources, and prompts with automatic schema generation and type safety.9Apache 2.0
- Flicense-qualityDmaintenanceMCP server to control a Flask application and optimize AWS costs, providing tools for app management, AWS resource checking, and cost analysis via Claude.3
- Flicense-qualityDmaintenanceA Flask-based reference implementation demonstrating how to build an MCP server with stateless HTTP transport, including example tools for generating random numbers and sentences.
- FlicenseAqualityDmaintenanceEnables text-to-image generation, image editing, and multi-image composition using Google's Gemini 2.5 Flash Image API. Supports flexible aspect ratios and character consistency across generations.1
- AlicenseCqualityDmaintenanceA universal Model Context Protocol implementation that serves as a semantic layer between LLMs and 3D creative software, providing a standardized interface for interacting with various Digital Content Creation tools through a unified API.16Apache 2.0
SkyXtools-Mcpofficial
Alicense-qualityCmaintenanceManual listener MCP server that bridges OpenCode with local security tools via a Flask HTTP service, enabling AI-assisted security operations.MIT- Alicense-qualityDmaintenanceAutomatically converts Python web backends (FastAPI, Flask, Django) into MCP servers by exposing API routes as MCP tools with near-zero boilerplate.MIT
- Alicense-qualityDmaintenanceA lightweight Flask-based server that enables Claude AI to perform real-time web searches via DuckDuckGo during conversations, allowing the AI to access current information.1MIT
- Alicense-qualityBmaintenanceGive your AI coding assistant live visibility into the user's browser. Claude sees the actual DOM, console errors, and network timing instead of guessing from screenshots. Drop-in middleware for FastAPI + Flask.MIT
- Alicense-qualityDmaintenanceAnalyzes API codebases from GitHub and Bitbucket repositories to generate Postman collections, business reports, and detailed code insights. Supports multiple frameworks including FastAPI, Spring Boot, Flask, Express, and OpenAPI/Swagger specifications.MIT
- Flicense-qualityDmaintenanceA dockerized Python MCP server that manages flash card projects using OpenAI embeddings and SQLite, enabling semantic search and storage of flash cards across projects.1
- Flicense-qualityCmaintenanceA Flask-based chatbot using Gemini 2.5 Flash and MCP tools to manage GitHub repositories and LinkedIn profiles via natural language.
- Flicense-qualityCmaintenanceA Model Context Protocol server that wraps the free GLM-4.6V-Flash vision model, enabling text-only LLM clients like Codex, Cursor, and Claude Desktop to analyze images, videos, and files (PDF/TXT) through standard MCP tools.2
- Flicense-qualityDmaintenanceA Flask-based server that hosts multiple tools, each exposing functionalities by calling external REST APIs through a unified interface.
- Flicense-qualityDmaintenanceFlask-based server that exposes callable tools via HTTP endpoints for AI agents like Gemini CLI, enabling agent orchestration, tool introspection, and workflow automation with a centralized tool registry.
- Flicense-qualityDmaintenanceA Flask-based server that implements Model Context Protocol to enhance LLMs with external tool capabilities via natural language, allowing tools like weather lookup and calculations to be invoked directly in the model's text output.2