Discover Awesome MCP Servers

gmail-mcp

A minimal MCP server that enables Claude to search, read, and manage Gmail messages and threads using official Google API libraries. It supports actions like sending emails, creating drafts, replying to threads, and managing labels through secure OAuth2 authentication.

instruckt-mcp

MCP server for instruckt visual annotations. Enables AI agents to retrieve pending annotations, view screenshots, and resolve annotations.

minimax-coding-plan-mcp

Node.js MCP server for MiniMax's Token Plan, providing image understanding and web search capabilities.

Image Generator

I can't directly generate and return an image using Together.ai (or any other service) within this text-based environment. I am a language model, not an image generation tool. However, I can provide you with the information you need to do it yourself. Here's what you'd typically need to do: 1. **Access Together.ai's API:** You'll need to sign up for an account on Together.ai and obtain an API key. This key is how you authenticate your requests. 2. **Use their API documentation:** Together.ai will have documentation on how to use their image generation API. This documentation will tell you: * **The endpoint (URL) to send your request to.** * **The required parameters:** This will almost certainly include a text prompt (the description of the image you want to generate). It might also include parameters for image size, style, number of images, etc. * **The format of the request (usually JSON).** * **The format of the response:** This will likely include a URL or data representing the generated image. 3. **Write code to make the API request:** You'll need to use a programming language (like Python) and a library that can make HTTP requests (like `requests` in Python) to send the request to Together.ai's API. 4. **Process the response:** Once you get the response from Together.ai, you'll need to parse it to extract the image data or URL. 5. **Display or save the image:** Finally, you can display the image in your application or save it to a file. **Example (Conceptual Python Code - Requires Together.ai API Key and Installation of `requests`):** ```python import requests import json # Replace with your actual Together.ai API key API_KEY = "YOUR_TOGETHERAI_API_KEY" def generate_image(prompt): """Generates an image using Together.ai based on the given prompt.""" url = "THE_TOGETHERAI_IMAGE_GENERATION_ENDPOINT" # Replace with the actual endpoint headers = { "Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json" } data = { "prompt": prompt, "width": 512, # Example: Image width "height": 512 # Example: Image height # Add other parameters as needed based on Together.ai's documentation } try: response = requests.post(url, headers=headers, data=json.dumps(data)) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) response_json = response.json() # Assuming the response contains a URL to the image image_url = response_json.get("image_url") # Adjust based on the actual response structure if image_url: print(f"Image URL: {image_url}") # You can then download the image using requests.get(image_url) # and save it to a file. Or display it in a GUI. return image_url # Or return the image data itself if that's what the API provides else: print("Error: Image URL not found in the response.") return None except requests.exceptions.RequestException as e: print(f"Error making API request: {e}") return None except json.JSONDecodeError: print("Error: Could not decode JSON response.") return None # Example usage: prompt = "A futuristic cityscape at sunset" image_url = generate_image(prompt) if image_url: print("Image generated successfully!") # Further processing of the image (download, display, etc.) else: print("Image generation failed.") ``` **Important Considerations:** * **API Documentation is Key:** The most important thing is to carefully read and understand Together.ai's API documentation. The code above is just a general example; you'll need to adapt it to their specific requirements. * **Error Handling:** The example includes basic error handling, but you should add more robust error handling to catch potential issues like network problems, invalid API keys, or incorrect parameters. * **Rate Limits:** Be aware of Together.ai's rate limits (how many requests you can make per minute/hour). You might need to implement logic to handle rate limiting. * **Cost:** Using image generation APIs often incurs costs. Understand Together.ai's pricing model before you start using the API extensively. **Translation to Spanish (of the explanation, not the code):** No puedo generar y devolver directamente una imagen usando Together.ai (o cualquier otro servicio) dentro de este entorno basado en texto. Soy un modelo de lenguaje, no una herramienta de generación de imágenes. Sin embargo, puedo proporcionarte la información que necesitas para hacerlo tú mismo. Esto es lo que normalmente necesitarías hacer: 1. **Acceder a la API de Together.ai:** Necesitarás registrarte para obtener una cuenta en Together.ai y obtener una clave API. Esta clave es cómo autenticas tus solicitudes. 2. **Usar su documentación de la API:** Together.ai tendrá documentación sobre cómo usar su API de generación de imágenes. Esta documentación te dirá: * **El endpoint (URL) al que enviar tu solicitud.** * **Los parámetros requeridos:** Esto casi seguro que incluirá un prompt de texto (la descripción de la imagen que quieres generar). También podría incluir parámetros para el tamaño de la imagen, el estilo, el número de imágenes, etc. * **El formato de la solicitud (normalmente JSON).** * **El formato de la respuesta:** Esto probablemente incluirá una URL o datos que representen la imagen generada. 3. **Escribir código para hacer la solicitud a la API:** Necesitarás usar un lenguaje de programación (como Python) y una biblioteca que pueda hacer solicitudes HTTP (como `requests` en Python) para enviar la solicitud a la API de Together.ai. 4. **Procesar la respuesta:** Una vez que obtengas la respuesta de Together.ai, necesitarás analizarla para extraer los datos de la imagen o la URL. 5. **Mostrar o guardar la imagen:** Finalmente, puedes mostrar la imagen en tu aplicación o guardarla en un archivo. **Consideraciones importantes:** * **La documentación de la API es clave:** Lo más importante es leer y comprender cuidadosamente la documentación de la API de Together.ai. El código anterior es solo un ejemplo general; necesitarás adaptarlo a sus requisitos específicos. * **Manejo de errores:** El ejemplo incluye un manejo básico de errores, pero debes agregar un manejo de errores más robusto para detectar posibles problemas como problemas de red, claves API no válidas o parámetros incorrectos. * **Límites de velocidad:** Ten en cuenta los límites de velocidad de Together.ai (cuántas solicitudes puedes hacer por minuto/hora). Es posible que debas implementar lógica para manejar la limitación de velocidad. * **Costo:** El uso de las API de generación de imágenes a menudo incurre en costos. Comprende el modelo de precios de Together.ai antes de comenzar a usar la API extensivamente.

Postgres MCP Pro

An open-source MCP server that provides AI agents with advanced PostgreSQL capabilities including index tuning, query plan optimization, and comprehensive database health analysis. It supports safe SQL execution through configurable access modes and offers both stdio and SSE transport options for various development environments.

Synlake MCP Server

Enables AI agents to discover, evaluate, and provision cloud infrastructure across AWS, GCP, and Azure with cross-cloud normalization, cost comparisons, and deployable execution kits.

Docling Granite MCP Server

Converts PDF documents to Markdown with automatic image description generation using IBM Granite Vision, supporting streaming and page range selection.

AVS Document Search System

A vector search system that enables semantic retrieval of document chunks using MongoDB Atlas Vector Search and Voyage AI embeddings, allowing users to search documents by meaning rather than just keywords.

vibecompass-mcp

MCP server that connects AI coding tools to VibeCompass projects for reading context and writing decisions, conflicts, and session notes.

remember-mcp

Multi-tenant memory system MCP server with vector search, relationships, and trust-based access control for AI assistants.

Monad NFT Launch Tool

An MCP server that helps users create NFT collections, deploy smart contracts to the Monad blockchain, and generate mint websites with Claude AI integration.

MCP Chat

A command-line interface application that enables interaction with LLMs through document retrieval, command-based prompts, and extensible tool integrations using the Model Control Protocol architecture.

buffer-mcp

MCP server for Buffer social media scheduling via the GraphQL API, enabling post creation, queue management, engagement metrics, and media uploads.

Azure AI Foundry MCP Server

Enables interaction with Azure AI Foundry services through a unified interface for model exploration and deployment, knowledge indexing and search, AI evaluation, and fine-tuning operations. Supports both GitHub token-based model testing and full Azure deployment workflows.

EGH Research MCP Server

Provides offline research and advanced search capabilities for Ellen Gould Harmon's writings via MCP and HTTP APIs, including PDF generation and Docker deployment.

Expense Tracker MCP

Enables tracking of personal expenses with tools to add, list, update, delete, and summarize expenses by category.

agent-validator-mcp-server

Enables testing and validation of APIs for AI agent compatibility, providing scores, grades, and actionable recommendations.

Bequall MCP Server

Enables AI assistants to provide information about Bequall's services for real estate, construction, and modular development, including company overview, use cases, and fit assessment.

Perplexity Web-Search MCP

Enables AI assistants to perform real-time web and academic searches using Perplexity's Sonar API.

Azure DevOps MCP Server

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps work items, projects, wikis, and boards through natural language.

mcp-toolkit-server

Converts Claude into a cybersecurity assistant by exposing 17 tools for network reconnaissance, cryptography, and security analysis, enabling users to perform tasks like SSL certificate checking, port scanning, and JWT analysis directly within conversations.

ssc

MCP server for scraping product prices, offers, reviews, and details from Amazon, Google Shopping, Bol.com, and Coolblue via natural language commands, with spend-cap protections.

1C MCP Toolkit

Integrates AI agents with 1C:Enterprise databases via MCP and REST API, supporting a built-in HTTP server (no Python required) or a Python proxy mode.

Garmin MCP Gateway

Multi-user OAuth 2.1 gateway allowing a trusted circle to connect their Garmin Connect accounts to Claude, enabling natural language access to Garmin tools.

openclaw-upgrade-orchestrator-mcp

Safe-upgrade advisor for OpenClaw. Detects current version, checks the deployment against a hand-curated catalog of version-specific known regressions, captures pre-upgrade snapshots, diffs them against post-upgrade state, and emits step-by-step upgrade + rollback guides.

mcp-meeting-rooms

Enables AI agents to browse, search, and book meeting rooms across multiple buildings with realistic seed data and conflict detection.

kolas-mcp

MCP server for Korea's KOLAS (Korean Laboratory Accreditation Scheme) under KATS. Search calibration / testing / inspection / medical-testing / reference-material-production / proficiency-testing accredited organizations and standards via knab.go.kr + data.go.kr.

novelai-mcp-server

Model Context Protocol (MCP) server for NovelAI image generation. Create high-quality anime art with advanced features like character positioning and V4 prompts.

gleif-mcp-server

A Model Context Protocol server that provides access to the GLEIF REST API for querying legal entity information, LEI records, issuer details, and organizational relationships.

Weather MCP Server

Provides current weather data and city comparisons for any location with support for metric/imperial units and optional forecasts.