Discover Awesome MCP Servers

Next.js MCP Server

Alat utilitas yang menganalisis rute aplikasi Next.js dan memberikan informasi detail tentang jalur API, metode HTTP, parameter, kode status, dan skema permintaan/respons.

Agent Knowledge MCP

A comprehensive Model Context Protocol server that integrates Elasticsearch search with file operations, document validation, and version control to transform AI assistants into powerful knowledge management systems.

Zuora MCP Server by CData

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Zuora (beta): https://www.cdata.com/download/download.aspx?sku=HZZK-V&type=beta

JIRA MCP Server

Enables AI assistants to search, view, create, and update JIRA issues using natural language commands and JQL queries.

GitHub API MCP Server

A Multi-Agent Conversation Protocol Server for the GitHub API, auto-generated using AG2's MCP builder, allowing users to interact with GitHub services through natural language.

HowToCook-MCP Server

An MCP server that transforms AI assistants into personal chefs by providing recipe recommendations and meal planning features based on the HowToCook repository.

MCP Add Server

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

mcp-confluence

Server konteks model yang menyediakan perintah yang dapat digunakan sebagai perintah garis miring (slash commands) untuk klien seperti Zed Editor, untuk menambahkan konten halaman sebagai konteks ke asisten AI.

Oracle MCP Server by CData

Oracle MCP Server by CData

MyMCP Prompt

MyMCP Prompt adalah alat untuk menghasilkan server Model Context Protocol (MCP) dari deskripsi bahasa alami. MVP ini menggunakan Google Gemini API untuk mengubah deskripsi pengguna menjadi server MCP Python fungsional dengan konfigurasi JSON yang sesuai.

Cisco ISE MCP Server

Enables management of Cisco Identity Services Engine (ISE) resources through the ERS API. Supports identity management, endpoint registration, network device configuration, and authorization profiles through natural language interactions.

solana-launchpads-mcp

An MCP server that tracks daily activity and graduate metrics across multiple Solana launchpads.

HubSpot MCP Server

Implementasi server yang memungkinkan asisten AI berinteraksi dengan data HubSpot CRM, memungkinkan pembuatan dan pengelolaan kontak dan perusahaan yang mulus, pengambilan riwayat aktivitas, dan akses ke data engagement melalui perintah bahasa alami.

富途 MCP 服务器 (Futu MCP Server)

Exposes Futu API client capabilities as an MCP (Model Context Protocol) tool, allowing AI assistants to access stock data from Futu through a standardized interface.

WeiWanMcpServer

私人McpServer

Slidespeak

Okay, here's a breakdown of how to generate PowerPoint presentations using the Slidespeak API, along with considerations and potential code examples (in Python, as it's a common language for API interaction): **Understanding the Slidespeak API** Before diving into code, you need to understand the core concepts of the Slidespeak API. I don't have direct access to the Slidespeak API documentation, so I'll make some educated assumptions based on common presentation API patterns. You'll need to **consult the official Slidespeak API documentation** for the *definitive* details. Here's what I'd expect: * **Authentication:** Most APIs require authentication. This usually involves an API key or token that you'll need to include in your requests. Find out how Slidespeak handles authentication. * **Presentation Structure:** The API will likely have a way to define the structure of your presentation. This will involve specifying: * **Slides:** Each slide in the presentation. * **Slide Layouts:** The layout of each slide (e.g., title slide, title and content, two content sections, etc.). Slidespeak will probably have predefined layout names or IDs. * **Elements:** The elements within each slide (e.g., text boxes, images, charts, shapes). You'll need to specify the type of element, its position, size, and content. * **Data Input:** You'll need to provide the data that will populate the presentation. This could be text, image URLs, chart data, etc. * **Output Format:** The API will likely allow you to specify the output format (e.g., `.pptx`, `.pdf`). * **Error Handling:** The API should provide error codes and messages to help you debug any issues. **General Steps for Generating a Presentation** 1. **Authentication:** Obtain your API key or token from Slidespeak. 2. **Define Presentation Structure:** Create a data structure (e.g., a Python dictionary or JSON object) that describes the presentation you want to generate. This will include the slides, layouts, and elements. 3. **Populate with Data:** Fill in the data for each element in the presentation. 4. **Make API Request:** Send a request to the Slidespeak API, including your authentication credentials and the presentation data. 5. **Handle Response:** Process the API response. If the request was successful, you'll receive a URL or a file containing the generated presentation. If there was an error, you'll need to handle it appropriately. **Example Python Code (Conceptual - Requires Slidespeak API Documentation)** ```python import requests import json # Replace with your actual Slidespeak API key API_KEY = "YOUR_SLIDESPEAK_API_KEY" API_ENDPOINT = "https://api.slidespeak.com/presentations" # Example endpoint def create_presentation(presentation_data): """ Creates a PowerPoint presentation using the Slidespeak API. Args: presentation_data: A dictionary containing the presentation structure and data. Returns: The URL of the generated presentation, or None if there was an error. """ headers = { "Authorization": f"Bearer {API_KEY}", # Or however Slidespeak authenticates "Content-Type": "application/json" } try: response = requests.post(API_ENDPOINT, headers=headers, data=json.dumps(presentation_data)) response.raise_for_status() # Raise HTTPError for bad responses (4xx or 5xx) response_json = response.json() presentation_url = response_json.get("presentation_url") # Adjust based on API response return presentation_url except requests.exceptions.RequestException as e: print(f"Error making API request: {e}") if response is not None: print(f"Response status code: {response.status_code}") print(f"Response body: {response.text}") # Print the error message from the API return None except json.JSONDecodeError as e: print(f"Error decoding JSON response: {e}") if response is not None: print(f"Response text: {response.text}") return None # Example presentation data (replace with your actual data) presentation_data = { "title": "My Awesome Presentation", "slides": [ { "layout": "title_slide", # Example layout name "title": "Introduction", "subtitle": "A brief overview" }, { "layout": "title_and_content", "title": "Key Points", "content": "Here are some important points to consider." } ] } # Create the presentation presentation_url = create_presentation(presentation_data) if presentation_url: print(f"Presentation created successfully! URL: {presentation_url}") else: print("Failed to create presentation.") ``` **Explanation of the Code:** 1. **Import Libraries:** Imports the `requests` library for making HTTP requests and the `json` library for working with JSON data. 2. **API Key and Endpoint:** Sets the API key and endpoint. **Replace these with the actual values from Slidespeak.** 3. **`create_presentation` Function:** * Takes `presentation_data` as input, which is a dictionary representing the presentation. * Sets the `headers` for the API request, including the `Authorization` header (using a bearer token, which is common) and the `Content-Type` header. * Uses a `try...except` block to handle potential errors during the API request. * Makes a `POST` request to the API endpoint using `requests.post()`. * Calls `response.raise_for_status()` to raise an exception if the response status code indicates an error (4xx or 5xx). * Parses the JSON response using `response.json()`. * Extracts the presentation URL from the JSON response (adjust the key based on the API's response format). * Handles `requests.exceptions.RequestException` (for network errors, timeouts, etc.) and `json.JSONDecodeError` (if the API returns invalid JSON). 4. **Example Presentation Data:** Creates a sample `presentation_data` dictionary. **This is where you'll need to define the structure and content of your presentation according to the Slidespeak API's specifications.** Pay close attention to the expected layout names and element types. 5. **Call the Function:** Calls the `create_presentation` function with the example data. 6. **Print Results:** Prints the URL of the generated presentation or an error message. **Important Considerations:** * **Slidespeak API Documentation:** **This is the most important thing.** You *must* consult the official Slidespeak API documentation to understand the exact format of the presentation data, the available layouts, the authentication method, and the API's response format. * **Error Handling:** Implement robust error handling to catch potential issues during the API request and processing. Print detailed error messages to help you debug. * **Data Validation:** Validate the data you're sending to the API to ensure that it conforms to the expected format. This can help prevent errors. * **Rate Limiting:** Be aware of any rate limits imposed by the Slidespeak API. If you exceed the rate limit, you may need to implement a retry mechanism. * **Asynchronous Operations:** For large presentations, the API might use asynchronous operations. This means that the API will return a task ID, and you'll need to poll the API periodically to check the status of the task. * **Layouts and Elements:** Carefully choose the appropriate layouts and elements for your presentation. The Slidespeak API documentation should provide a list of available layouts and element types. * **Image Handling:** If you're including images in your presentation, make sure that the image URLs are publicly accessible. The Slidespeak API may also have specific requirements for image formats and sizes. **How to Adapt the Code:** 1. **Replace Placeholders:** Replace the placeholder values for `API_KEY` and `API_ENDPOINT` with your actual Slidespeak API credentials. 2. **Define Presentation Data:** Modify the `presentation_data` dictionary to match the structure and content of your desired presentation. Refer to the Slidespeak API documentation for the correct format. 3. **Adjust Authentication:** If Slidespeak uses a different authentication method (e.g., API key in the query string), adjust the `headers` accordingly. 4. **Handle API Response:** Modify the code that extracts the presentation URL from the API response to match the actual response format. 5. **Add Error Handling:** Add more specific error handling based on the error codes and messages returned by the Slidespeak API. **In summary, generating PowerPoint presentations with the Slidespeak API requires a thorough understanding of the API's documentation, careful construction of the presentation data, and robust error handling. Use the example code as a starting point and adapt it to your specific needs.**

Gradle Tomcat MCP Server

Enables management of Gradle-based Tomcat applications with capabilities for starting, stopping, restarting processes and querying application logs.

BluestoneApps Development Standards (Remote)

Menerapkan Model Context Protocol (MCP) melalui HTTP untuk menyediakan akses jarak jauh ke standar pengkodean BluestoneApps dan contoh kode React Native.

Google Calendar MCP Server

Server Protokol Konteks Model yang menyediakan akses tanpa hambatan ke Google Calendar API dengan dukungan operasi asinkron, memungkinkan pengelolaan kalender yang efisien melalui antarmuka terstandarisasi.

Shopify Python MCP Server

Server MCP yang terintegrasi dengan Shopify API, memungkinkan pengguna Claude Desktop untuk mengambil dan memanipulasi informasi produk dari toko Shopify.

Task Trellis MCP

An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.

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 Twitter

Server Protokol Konteks Model yang memungkinkan model dan aplikasi AI berinteraksi langsung dengan Twitter/X, menyediakan kemampuan untuk membuat postingan, membalas tweet, mengambil data pengguna, dan mengelola tindakan akun.

Agentic MCP Server

Enables AI-driven orchestration of GitHub development workflows including automated issue analysis, code generation, code review, and PR creation through multiple specialized agents. Integrates with GitHub Actions to automate the complete development process from issue to pull request.

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

"Install semua dependensi (dependencies) untuk server MCP."

MCP Atlassian Server

A Model Context Protocol server that connects AI assistants like Cline to Atlassian Jira and Confluence, enabling them to query data and perform actions through a standardized interface.

MCP OpenAI Image Generation Server

Enables AI assistants to generate and edit images through OpenAI's DALL-E models via MCP tools. Supports text-to-image generation and image-to-image editing with configurable parameters for size, quality, and style.