Discover Awesome MCP Servers

AutoBrowser MCP

Autobrowser MCP is a Model Context Provider (MCP) server that allows AI applications to control your browser

MCP4GVA

Enables access to GVA GIS (Generalitat Valenciana) geographic data through ArcGIS REST API, allowing queries, filtering, and exporting of land activity information in the Valencian Community.

MCP Notion Server

MCP server for using the Notion API

Slidespeak

Okay, I understand. You want to know how to generate PowerPoint presentations using the Slidespeak API. Here's a breakdown of how to do that, along with important considerations: **Understanding the Slidespeak API** The Slidespeak API allows you to programmatically create and manipulate PowerPoint presentations. You'll typically interact with it using HTTP requests (like POST, GET, PUT, DELETE) to send instructions and receive responses. **General Steps to Generate a PowerPoint Presentation** 1. **Sign Up and Get an API Key:** * You'll need to create an account on the Slidespeak platform and obtain an API key. This key is essential for authenticating your requests. The Slidespeak documentation will guide you through this process. 2. **Choose a Programming Language and Library:** * Select a programming language you're comfortable with (e.g., Python, JavaScript, Java, PHP, Ruby). * Use an HTTP client library in your chosen language to make requests to the Slidespeak API. Examples: * **Python:** `requests` * **JavaScript:** `fetch`, `axios` * **Java:** `HttpClient` (from Apache HttpComponents) * **PHP:** `curl` * **Ruby:** `net/http` 3. **Understand the Slidespeak API Endpoints and Data Structures:** * **Crucially, consult the Slidespeak API documentation.** This is the most important step. The documentation will tell you: * The base URL for the API. * The specific endpoints for creating presentations, adding slides, adding text, images, etc. * The format of the data you need to send in your requests (usually JSON). * The format of the responses you'll receive. * Authentication methods (usually using your API key in a header). 4. **Construct Your API Requests:** * **Create a Presentation:** Typically, you'll start by making a POST request to an endpoint like `/presentations` or `/createPresentation`. You might provide a title for the presentation in the request body. * **Add Slides:** Next, you'll add slides to the presentation. This usually involves a POST request to an endpoint like `/presentations/{presentationId}/slides` or `/addSlide`. You might specify a layout for the slide (e.g., title slide, title and content, blank). * **Add Content to Slides:** For each slide, you'll add text, images, shapes, etc. This will involve POST or PUT requests to endpoints like `/slides/{slideId}/text`, `/slides/{slideId}/image`, `/slides/{slideId}/shape`. You'll need to provide the content (text, image URL, shape type, etc.) and positioning information (coordinates, size). * **Set Formatting:** You can usually control the formatting of text, shapes, and other elements (font, color, size, alignment, etc.) through the API. The Slidespeak documentation will detail the available formatting options. * **Download the Presentation:** Finally, you'll make a GET request to an endpoint like `/presentations/{presentationId}/download` or `/presentations/{presentationId}.pptx` to download the generated PowerPoint file. 5. **Handle API Responses:** * Check the HTTP status code of each response. A status code of 200 (OK) usually indicates success. Other status codes (e.g., 400 Bad Request, 401 Unauthorized, 500 Internal Server Error) indicate errors. * Parse the response body (usually JSON) to extract any relevant information, such as the ID of the created presentation or slide. * Implement error handling to gracefully handle API errors. **Example (Conceptual - Python with `requests`)** ```python import requests import json API_KEY = "YOUR_SLIDESPEAK_API_KEY" # Replace with your actual API key BASE_URL = "https://api.slidespeak.com/v1" # Replace with the actual Slidespeak API base URL def create_presentation(title): url = f"{BASE_URL}/presentations" headers = { "Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json" } data = {"title": title} response = requests.post(url, headers=headers, data=json.dumps(data)) if response.status_code == 201: # Assuming 201 Created is the success code return response.json()["id"] # Assuming the response contains the presentation ID else: print(f"Error creating presentation: {response.status_code} - {response.text}") return None def add_slide(presentation_id, layout="title_and_content"): url = f"{BASE_URL}/presentations/{presentation_id}/slides" headers = { "Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json" } data = {"layout": layout} response = requests.post(url, headers=headers, data=json.dumps(data)) if response.status_code == 201: return response.json()["id"] # Assuming the response contains the slide ID else: print(f"Error adding slide: {response.status_code} - {response.text}") return None def add_text_to_slide(slide_id, text, x, y, width, height): url = f"{BASE_URL}/slides/{slide_id}/text" headers = { "Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json" } data = { "text": text, "x": x, "y": y, "width": width, "height": height } response = requests.post(url, headers=headers, data=json.dumps(data)) if response.status_code == 200: return True else: print(f"Error adding text: {response.status_code} - {response.text}") return False def download_presentation(presentation_id, filename="presentation.pptx"): url = f"{BASE_URL}/presentations/{presentation_id}/download" # Or maybe f"{BASE_URL}/presentations/{presentation_id}.pptx" headers = { "Authorization": f"Bearer {API_KEY}" } response = requests.get(url, headers=headers, stream=True) # stream=True for large files if response.status_code == 200: with open(filename, "wb") as f: for chunk in response.iter_content(chunk_size=8192): f.write(chunk) print(f"Presentation downloaded to {filename}") return True else: print(f"Error downloading presentation: {response.status_code} - {response.text}") return False # Example Usage presentation_id = create_presentation("My Awesome Presentation") if presentation_id: slide_id = add_slide(presentation_id) if slide_id: add_text_to_slide(slide_id, "Hello, Slidespeak!", 100, 100, 500, 50) download_presentation(presentation_id) ``` **Important Considerations and Best Practices:** * **Rate Limiting:** Be aware of the Slidespeak API's rate limits. If you exceed the limits, your requests may be throttled or blocked. Implement error handling and retry mechanisms to deal with rate limiting. * **Error Handling:** Implement robust error handling to catch API errors and handle them gracefully. Log errors for debugging purposes. * **Data Validation:** Validate the data you're sending to the API to ensure it's in the correct format and within the allowed ranges. * **Asynchronous Operations:** For complex presentations, consider using asynchronous operations to avoid blocking your main thread. This is especially important for web applications. * **API Documentation is Key:** I cannot stress this enough. The Slidespeak API documentation is your bible. Refer to it constantly. The example code above is *illustrative* and *will not work* without the correct API endpoints and data structures from the Slidespeak documentation. * **Security:** Protect your API key. Do not hardcode it directly into your code, especially if you're sharing your code publicly. Use environment variables or a configuration file to store your API key. * **Testing:** Thoroughly test your code to ensure it generates presentations correctly and handles errors gracefully. **In summary, to use the Slidespeak API, you need to:** 1. **Get an API key.** 2. **Study the Slidespeak API documentation.** 3. **Use a programming language and HTTP client library to make requests to the API.** 4. **Construct your requests according to the API documentation.** 5. **Handle the API responses and errors.** Good luck! Let me know if you have more specific questions after reviewing the Slidespeak API documentation.

OpenCollective MCP Server

Provides programmatic access to OpenCollective and Hetzner Cloud to automate bookkeeping, collective management, and invoice handling. It enables AI agents to manage expenses, query transactions, and automatically reconcile hosting invoices without manual intervention.

Momento MCP Server

Enables interaction with Momento Cache to manage cache entries and perform administrative tasks like creating, listing, or deleting caches. It provides tools for getting and setting values with configurable TTLs through a serverless caching infrastructure.

Obsidian MCP Tools

A read-only toolkit for searching and analyzing Markdown note directories and Obsidian vaults through AI clients. It enables metadata extraction, full-text search, and natural language querying of note content, tags, and backlinks.

Remote MCP Server (Authless)

A tool for deploying an authentication-free Model Context Protocol server on Cloudflare Workers that can be connected to AI clients like Claude Desktop or the Cloudflare AI Playground.

tavily-mcp

tavily-mcp

Microsoft Graph MCP Server

Enables management of Microsoft 365 users, licenses, and groups through Microsoft Graph API. Supports user provisioning, license assignment, group management, and automated M365 administration workflows.

Home Assistant MCP Server

Controle de Dispositivos Inteligentes 🎮 💡 Luzes: Brilho, cor, RGB 🌡️ Clima: Temperatura, HVAC, umidade 🚪 Persianas/Cortinas: Posição e inclinação 🔌 Interruptores: Liga/Desliga 🚨 Sensores: Monitoramento de estado Organização Inteligente 🏠 Agrupamento com reconhecimento de contexto. Arquitetura Robusta 🛠️ Tratamento de erros, validação de estado...

PAMPA

Provides semantic code search and retrieval capabilities for AI agents, enabling them to query codebases using natural language with automatic learning, hybrid search, and intelligent chunking of functions and classes.

Remote MCP Server on Cloudflare

A Model Context Protocol server that runs on Cloudflare Workers with OAuth login, allowing clients like Claude Desktop to connect to it for tool-augmented AI interactions.

epsg-mcp

An MCP server that provides knowledge about Coordinate Reference Systems (CRS).

MCP Project Context Server

A persistent memory layer for Claude Code that maintains project information, technology stack, tasks, decisions, and session history between coding sessions, eliminating the need to re-explain project context.

mcp_repo_c11db53a

Este é um repositório de teste criado pelo script de teste do Servidor MCP para o GitHub.

ArXiv MCP Server

Uma ponte entre assistentes de IA e o repositório de pesquisa ArXiv que permite pesquisar, baixar e ler artigos acadêmicos através do Protocolo de Controle de Mensagens.

Web3 MCP Server

Servidor Web3 MCP para cadeias EVM (no momento)

Zilliz MCP Server

Enables AI agents to interact with Milvus vector databases and Zilliz Cloud through natural language, allowing users to create clusters, manage collections, insert vector data, and perform semantic searches directly from their AI assistants.

Cloudflare Playwright MCP

A server that enables AI assistants to control a browser through tools, allowing them to perform web automation tasks like navigation, typing, clicking, and taking screenshots.

mcp-server-webcrawl

Bridge the gap between your web crawl and AI language models. With mcp-server-webcrawl, your AI client filters and analyzes web content under your direction or autonomously, extracting insights from your web content. Supports WARC, wget, InterroBot, Katana, and SiteOne crawlers.

Self-hosted LLM MCP Server

Enables interaction with self-hosted LLM models via Ollama and Supabase database operations. Supports text generation, SQL queries, and data storage/retrieval through natural language commands.

MCP Dependencies Installer

Instalar todas as dependências para o servidor MCP.

Webshot MCP

Enables taking screenshots of web pages with support for multiple devices (desktop, mobile, tablet), custom dimensions, full-page capture, and various image formats. Built with Playwright for reliable web page rendering and screenshot generation.

MCP Search Server

An MCP server that provides semantic search capabilities by integrating with an OpenSearch-based search service. It enables users to perform complex document searches across multiple indices with support for advanced filtering and robust error handling.

MCP Add Server

A minimal Model Context Protocol server that provides a simple add(a, b) tool for computing the sum of two numbers.

Nanoleaf MCP Server

A Model Context Protocol server that enables controlling Nanoleaf smart lights through Warp terminal or any MCP-compatible client, providing tools for device discovery, authorization, and control of lights, brightness, colors, and effects.