"Flask" matching MCP servers:

Flask Extension for apcore (AI-Perceivable Core) integration. Expose your Flask routes as MCP tools with auto-discovery, Pydantic schema inference, and built-in observability.

Provides a collection of MCP servers for computational chemistry tasks including molecular generation and retrosynthesis. Also offers property prediction and molecule pricing capabilities.

Flask-based Model Context Protocol (MCP) server for Python. Drop it into any Flask app or run it standalone.

Flask-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.

Video feedback for AI agents via Flask (flask.do). Agents upload renders for human review and get the feedback back as transcribed, timestamped comments over MCP, with annotated frames and versioned revisions.

MCP server to control a Flask application and optimize AWS costs, providing tools for app management, AWS resource checking, and cost analysis via Claude.

A Flask-based reference implementation demonstrating how to build an MCP server with stateless HTTP transport, including example tools for generating random numbers and sentences.

A 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.

A deterministic video rendering engine that enables AI agents to create programmable, reproducible videos via MCP protocol.

Live sports betting player props MCP server covering NBA, MLB, NFL, NHL, NCAA, and soccer. Unified from real sportsbooks into one REST API and a real MCP server (Streamable HTTP). Free tier, no card required.

Enables 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.

Enables MCP-compatible IDEs to generate images and videos using Agnes 2.5 flash models through natural language prompts, with tools for image generation, asynchronous video creation, and video polling.

Enables AI coding agents to make fast, zero-output-token decisions by evaluating context, diffs, logs, or options through the OpenRouter Decisions API using TypeSafe Jev, returning calibrated probabilities for binary, categorical, or scoring questions.

A unified MCP server for scaffolding project structures across multiple frameworks including Spring Boot, React, Vue, Next.js, FastAPI, Django, Flask, Express, and more.

Arbitrage detection across DEXes on Base. Scan pairs, detect price gaps, estimate profit, simulate flash loan routes.

Enables conversational image generation and editing with Google's Gemini 2.5 Flash Image Preview. Supports text-to-image generation, natural language image editing, multi-image composition, and style transfer with optional file saving.

Enables AI agents to inspect, modify, run, and debug Godot projects, including scene and script analysis, editor and project management, and visual verification through screenshots.

Enables comprehensive security vulnerability scanning and code quality analysis for Python applications. Provides detailed reports with scoring, actionable suggestions, and comparison tracking specifically designed for backend developers working with frameworks like Django, Flask, and FastAPI.

A 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.

Manual listener MCP server that bridges OpenCode with local security tools via a Flask HTTP service, enabling AI-assisted security operations.