Databricks MCP Server - Alternatives & Competitors

Ranked by Relevance

• 1
  

  Databricks Genie MCP Server

  Bridge natural language queries to Databricks Genie via Model Context Protocol.

  Databricks Genie MCP Server enables interaction between large language models and the Databricks Genie API using the Model Context Protocol. It allows users to ask natural language questions, start and manage conversations, and run SQL queries in Genie spaces. The tool provides structured results, supports follow-up queries, and facilitates connection through both standard and Docker-based setups. Designed for use with Claude Desktop, it streamlines conversational analytics within Databricks workspaces.

  12 2 MCP
• 2
  

  TeslaMate MCP Server

  Query your TeslaMate data using the Model Context Protocol

  TeslaMate MCP Server implements the Model Context Protocol to enable AI assistants and clients to securely access and query Tesla vehicle data, statistics, and analytics from a TeslaMate PostgreSQL database. The server exposes a suite of tools for retrieving vehicle status, driving history, charging sessions, battery health, and more using standardized MCP endpoints. It supports local and Docker deployments, includes bearer token authentication, and is intended for integration with MCP-compatible AI systems like Claude Desktop.

  106 14 MCP
• 3
  

  MCP Server for ZenML

  Expose ZenML data and pipeline operations via the Model Context Protocol.

  Implements a Model Context Protocol (MCP) server for interfacing with the ZenML API, enabling standardized access to ZenML resources for AI applications. Provides tools for reading data about users, stacks, pipelines, runs, and artifacts, as well as triggering new pipeline runs if templates are available. Includes robust testing, automated quality checks, and supports secure connection from compatible MCP clients. Designed for easy integration with ZenML instances, supporting both local and remote ZenML deployments.

  32 10 MCP
• 4
  

  Teamwork MCP Server

  Seamless Teamwork.com integration for Large Language Models via the Model Context Protocol

  Teamwork MCP Server is an implementation of the Model Context Protocol (MCP) that enables Large Language Models to interact securely and programmatically with Teamwork.com. It offers standardized interfaces, including HTTP and STDIO, allowing AI agents to perform various project management operations. The server supports multiple authentication methods, an extensible toolset architecture, and is designed for production deployments. It provides read-only capability for safe integrations and robust observability features.

  11 9 MCP
• 5
  

  Pydantic Logfire MCP Server

  Enables LLMs to access and analyze application telemetry data through standardized MCP tools.

  Pydantic Logfire MCP Server provides an MCP-compatible interface to access, analyze, and query telemetry data sent to Pydantic Logfire. It allows LLMs to retrieve distributed traces, perform SQL queries on telemetry databases, and generate links for trace inspection. The server can be integrated with well-known MCP clients and supports configuration for secure access with read tokens.

  124 21 MCP
• 6
  

  mcp-graphql

  Enables LLMs to interact dynamically with GraphQL APIs via Model Context Protocol.

  mcp-graphql provides a Model Context Protocol (MCP) server that allows large language models to discover and interact with GraphQL APIs. The implementation facilitates schema introspection, exposes the GraphQL schema as a resource, and enables secure query and mutation execution based on configuration. It supports configuration through environment variables, automated or manual installation options, and offers flexibility in using local or remote schema files. By default, mutation operations are disabled for security, but can be enabled if required.

  319 54 MCP
• 7
  

  CyberChef API MCP Server

  MCP server enabling LLMs to access CyberChef's powerful data analysis and processing tools.

  CyberChef API MCP Server implements the Model Context Protocol (MCP), interfacing with the CyberChef Server API to provide structured tools and resources for LLM/MCP clients. It exposes key CyberChef operations such as executing recipes, batch processing, retrieving operation categories, and utilizing the magic operation for automated data decoding. The server can be configured and managed via standard MCP client workflows and supports context-driven tool invocation for large language models.

  29 5 MCP
• 8
  

  Catalysis Hub MCP Server

  MCP-compliant server for accessing catalysis research data via GraphQL.

  Catalysis Hub MCP Server provides a Model Context Protocol interface to the Catalysis Hub's GraphQL API, enabling seamless programmatic access to catalyst research datasets. It allows users to execute flexible and complex GraphQL queries to retrieve reaction, material, and publication data. The server supports robust error handling, parameterized queries, and is designed for interoperability with AI agents in scientific workflows.

  1 3 MCP
• 9
  

  Dune Analytics MCP Server

  Bridge Dune Analytics data seamlessly to AI agents via a Model Context Protocol server.

  Dune Analytics MCP Server provides a Model Context Protocol-compliant server that allows AI agents to access and interact with Dune Analytics data. It exposes tools to fetch the latest results of Dune queries and execute arbitrary queries, returning results in CSV format. The server is easily deployable, supports integration with platforms like Claude Desktop, and requires a Dune Analytics API key for operation.

  31 8 MCP
• 10
  

  MLB API MCP Server

  A Model Context Protocol server for seamless MLB data access through AI applications.

  MLB API MCP Server provides comprehensive access to MLB statistics and baseball data via a FastMCP-based interface. It exposes a range of MLB functionalities—including live game data, player statistics, team information, and advanced metrics—as MCP tools accessible by AI workflows. Compatible with MCP-enabled AI clients, it enables structured, schema-validated querying and integrations for baseball data.

  33 9 MCP
• 11
  

  MXCP

  Enterprise-Grade Model Context Protocol Framework for AI Applications

  MXCP is an enterprise-ready framework that implements the Model Context Protocol (MCP) for building secure, production-grade AI application servers. It introduces a structured methodology focused on data modeling, robust service design, policy enforcement, and comprehensive testing, integrated with strong security and audit capabilities. The framework enables rapid development and deployment of AI tools, supporting both SQL and Python environments, with built-in telemetry and drift detection for reliability and compliance.

  49 6 MCP
• 12
  

  mcp-server-apache-airflow

  A Model Context Protocol server for integrating Apache Airflow with MCP clients.

  mcp-server-apache-airflow provides a Model Context Protocol (MCP) server implementation that allows standardized interaction with Apache Airflow environments. By wrapping Airflow's REST API, it enables MCP clients to manage and orchestrate workflows, DAGs, and runs in a consistent and interoperable manner. This implementation leverages the official Apache Airflow client library to ensure robust compatibility and maintainability. It streamlines the management of Airflow resources by exposing comprehensive endpoint coverage for key workflow operations.

  109 28 MCP
• 13
  

  QA Sphere MCP Server

  Model Context Protocol server enabling LLMs to interact with QA Sphere test cases

  QA Sphere MCP Server provides a Model Context Protocol (MCP) integration for QA Sphere, allowing Large Language Models to interact with, discover, and summarize test cases within the QA Sphere test management system. It enables AI-powered IDEs and MCP clients to reference and manipulate QA Sphere test case data within development workflows. The solution supports quick integration into clients like Claude, Cursor, and 5ire, facilitating seamless collaboration and context sharing for AI-assisted development.

  15 6 MCP
• 14
  

  Firefly MCP Server

  Seamless resource discovery and codification for Cloud and SaaS with Model Context Protocol integration.

  Firefly MCP Server is a TypeScript-based server implementing the Model Context Protocol to enable integration with the Firefly platform for discovering and managing resources across Cloud and SaaS accounts. It supports secure authentication, resource codification into infrastructure as code, and easy integration with tools such as Claude and Cursor. The server can be configured via environment variables or command line and communicates using standardized MCP interfaces. Its features facilitate automation and codification workflows for cloud resource management.

  15 6 MCP
• 15
  

  Thales CDSP CRDP MCP Server

  MCP server enabling secure data protection and revelation with Thales CipherTrust CRDP

  Thales CDSP CRDP MCP Server implements the Model Context Protocol (MCP) to allow AI applications and LLMs to securely protect and reveal sensitive data via Thales CipherTrust RestFul Data Protection (CRDP) service. The server supports both stdio and HTTP transports, individual and bulk data operations, and robust versioning support. Features include health checks, metrics collection, and integration with protection policies and JWT-based authorization.

  2 3 MCP
• 16
  

  TickTick MCP

  MCP server for AI-powered TickTick task management integration

  TickTick MCP is a Model Context Protocol (MCP) server that enables standardized integration of TickTick's task management features with AI assistants and developer applications. It allows programmatic access to create, update, retrieve, complete, or delete tasks and projects in TickTick via Python. Using this MCP server, AI systems can leverage TickTick's API to help automate and manage user's to-do lists and projects through natural language or other interfaces.

  6 6 MCP
• 17
  

  Alkemi MCP Server

  Integrate Alkemi Data sources with MCP Clients for seamless, standardized data querying.

  Alkemi MCP Server provides a STDIO wrapper for connecting Alkemi data sources—including Snowflake, Google BigQuery, and Databricks—with MCP Clients using the Model Context Protocol. It facilitates context sharing, database metadata management, and query generation through a standardized protocol endpoint. Shared MCP Servers allow teams to maintain consistent, high-quality data querying capabilities without needing to replicate schemas or query knowledge for each agent. Out-of-the-box integration with Claude Desktop and robust debugging tools are also included.

  2 1 MCP
• 18
  

  Perplexity MCP Server

  MCP Server integration for accessing the Perplexity API with context-aware chat completion.

  Perplexity MCP Server provides a Model Context Protocol (MCP) compliant server that interfaces with the Perplexity API, enabling chat completion with citations. Designed for seamless integration with clients such as Claude Desktop, it allows users to send queries and receive context-rich responses from Perplexity. Environment configuration for API key management is supported, and limitations with long-running requests are noted. Future updates are planned to enhance support for client progress reporting.

  85 35 MCP
• 19
  

  TickTick MCP Server

  Enable powerful AI-driven task management for TickTick via the Model Context Protocol.

  TickTick MCP Server provides comprehensive programmatic access to TickTick task management features using the Model Context Protocol. Built on the ticktick-py library, it enables AI assistants and MCP-compatible applications to create, update, retrieve, and filter tasks with improved precision and flexibility. The server supports advanced filtering, project and tag management, subtask handling, and robust context management for seamless AI integration.

  35 9 MCP
• 20
  

  Label Studio MCP Server

  Bridge between Model Context Protocol clients and Label Studio for project, task, and prediction management.

  Label Studio MCP Server implements a Model Context Protocol (MCP) interface to enable programmatic management of Label Studio projects, tasks, and model predictions. It enables structured interactions with a running Label Studio instance via MCP clients, supports various project and task operations, and integrates the official Label Studio SDK. The tool exposes multiple functions for project management, task handling, and prediction integration, allowing both natural language and structured API calls.

  23 8 MCP
• 21
  

  MetaTrader MCP Server

  Let AI assistants trade for you using natural language.

  MetaTrader MCP Server is a bridge that connects AI assistants such as Claude and ChatGPT to the MetaTrader 5 trading platform via the Model Context Protocol (MCP). It enables users to perform trading actions on MetaTrader 5 through natural language instructions. The system supports real-time data access, full account management, and secure local credential handling, offering both MCP and REST API interfaces.

  120 34 MCP
• 22
  

  dbt-docs-mcp

  MCP server for querying dbt project metadata and lineage

  dbt-docs-mcp implements a Model Context Protocol (MCP) server that interacts with dbt project metadata artifacts such as manifest.json and catalog.json. It exposes the dbt project graph through a standardized API, enabling search and inspection of models, sources, columns, and their upstream/downstream lineage. The solution facilitates column-level and model-level lineage analysis, node inspection, and can be extended to support database metadata querying and custom knowledge bases. It is designed for integrations with MCP-compatible clients, supporting advanced data discovery and context sharing workflows.

  21 5 MCP
• 23
  

  MCP Server for Data Exploration

  Interactive Data Exploration and Analysis via Model Context Protocol

  MCP Server for Data Exploration enables users to interactively explore and analyze complex datasets using prompt templates and tools within the Model Context Protocol ecosystem. Designed as a personal Data Scientist assistant, it facilitates the conversion of raw data into actionable insights without manual intervention. Users can load CSV datasets, run Python scripts, and generate tailored reports and visualizations through an AI-powered interface. The server integrates directly with Claude Desktop, supporting rapid setup and seamless usage for both macOS and Windows.

  503 63 MCP
• 24
  

  metoro-mcp-server

  Bridge Kubernetes observability data to LLMs via the Model Context Protocol.

  Metoro MCP Server is an implementation of the Model Context Protocol (MCP) that enables seamless integration between Kubernetes observability data and large language models. It connects Metoro’s eBPF-based telemetry APIs to LLM applications such as the Claude Desktop App, allowing AI systems to query and analyze Kubernetes clusters. This solution supports both authenticated and demo modes for accessing real-time cluster insights.

  45 12 MCP
• 25
  

  Web3 Jobs MCP Server

  AI-ready MCP server delivering curated, real-time Web3 job listings.

  Web3 Jobs MCP Server provides real-time access to curated Web3 job listings from web3.career through a Model Context Protocol (MCP) interface, enabling intelligent job discovery for AI agents. The server supports advanced filtering by location, remote status, job tag, and result limits, and returns results in Markdown format. It enables the generation of natural language prompts for job searches, facilitating seamless integration with AI platforms such as Claude Desktop. Designed for Python 3.10+, it offers flexible deployment and configuration options.

  4 3 MCP
• 26
  

  Kaggle MCP Server

  Model Context Protocol server enabling Kaggle dataset search and download tools.

  Kaggle MCP Server implements the Model Context Protocol (MCP) using the fastmcp library and provides tools for searching and downloading datasets from Kaggle via a standardized MCP interface. It manages Kaggle API authentication, exposes search and download tools as MCP resources, and offers prompts for generating exploratory data analysis notebooks. The server can be run locally or via Docker, supporting easy integration with MCP clients and compliant applications.

  28 7 MCP
• 27
  

  Signoz MCP Server

  Connect SigNoz observability data to AI assistants via the Model Context Protocol.

  Signoz MCP Server acts as a bridge between SigNoz observability platforms and AI assistants by implementing the Model Context Protocol (MCP). It exposes a suite of tools for querying dashboard information, fetching panel and metrics data, executing custom queries, and retrieving traces or logs from SigNoz. The tool supports integration with popular AI assistants, flexible deployment options (Docker, local virtual environments), and secure configuration via environment variables or YAML files. The server is designed to enable standardized programmatic context retrieval for enhancing AI/LLM workflows.

  11 1 MCP
• 28
  

  Web3 MCP

  A Model Context Protocol server for unified blockchain data access.

  Web3 MCP is a Model Context Protocol server that provides access to blockchain data through Ankr's Advanced API. It allows large language models to interact seamlessly with multiple blockchain networks such as Ethereum, BSC, Polygon, and Avalanche. With support for NFT, token, and blockchain query APIs, it enables users and AI agents to retrieve on-chain data, statistics, and analytics efficiently within an MCP context.

  3 1 MCP
• 29
  

  solscan-mcp

  A Rust-based MCP server for querying Solscan Pro API on Solana blockchain data.

  solscan-mcp provides a Model Context Protocol (MCP) server that interfaces with the Solscan Pro API to deliver blockchain data from the Solana network. Built in Rust, it allows querying of token information, account activities, and transactions, and is designed for easy integration with language models. The tool supports context-driven investigations by leveraging AI to analyze and report on blockchain wallet behaviors using customized context inputs.

  32 12 MCP
• 30
  

  mcp-server-sql-analyzer

  MCP server for SQL analysis, linting, and dialect conversion.

  Provides standardized MCP server capabilities for analyzing, linting, and converting SQL queries across multiple dialects using SQLGlot. Supports syntactic validation, dialect transpilation, extraction of table and column references, and offers tools for understanding query structures. Facilitates seamless workflow integration with AI assistants through a set of MCP tools.

  26 5 MCP
• 31
  

  Postmancer

  A standalone MCP server for API testing and management via AI assistants.

  Postmancer is a Model Context Protocol (MCP) server designed to facilitate API testing and management through natural language interactions with AI assistants. It enables HTTP requests, organizes API endpoints into collections, and provides tools for managing environment variables, authentication, and request history. Postmancer is particularly aimed at integrating with AI platforms like Claude for seamless, automated API workflows.

  28 4 MCP
• 32
  

  TrackMage MCP Server

  Shipment and logistics tracking MCP server with multi-carrier support.

  TrackMage MCP Server implements the Model Context Protocol (MCP) to provide shipment tracking, logistics management, and API integration for over 1,600 carriers worldwide. It allows integration with major LLMs, supports resources such as workspaces, shipments, orders, carriers, and tracking statuses, and offers tools to create, update, and monitor shipments and orders. The server supports OAuth-based authentication, flexible configuration via environment variables, and can be deployed locally for customized logistics operations.

  1 4 MCP
• 33
  

  MCP GitLab Jira Server

  MCP server for seamless GitLab and Jira integration

  MCP GitLab Jira Server acts as a bridge, enabling AI agents to interact programmatically with GitLab and Jira instances via the Model Context Protocol. It provides a standardized server interface for operations on projects, merge requests, pipelines, branches, issues, releases, and users in GitLab, as well as tickets and project management features in Jira. The server can be run as a CLI tool or in a Docker container, making it compatible with tools like gemini-cli. Configuration via environment variables allows secure authentication and flexible deployment.

  6 4 MCP
• 34
  

  Shopify Storefront MCP Server

  Seamless Shopify Storefront API access for AI assistants via Model Context Protocol

  Enables AI assistants to interact with Shopify store data through standardized MCP tools. Offers endpoints for product discovery, inventory management, GraphQL queries, cart operations, and comprehensive customer data manipulation. Designed for easy integration with MCP-compatible AI and automated token handling. Simplifies secure connection to Shopify's Storefront API with minimal configuration.

  5 5 MCP
• 35
  

  ROADrecon MCP Server

  Expose ROADRecon Azure AD data to AI assistants for advanced security analysis.

  ROADrecon MCP Server implements the Model Context Protocol to provide seamless access to Azure AD data from ROADRecon instances for AI assistants like Claude. It enables secure retrieval and analysis of directory data, offers pre-built security analysis tools, and supplies prompt templates for common security tasks. The server facilitates structured data access and tool execution, streamlining organizational security reviews.

  47 8 MCP
• 36
  

  Excel MCP Server

  Manipulate Excel files programmatically via the Model Context Protocol.

  Excel MCP Server enables AI agents and applications to create, read, and modify Excel workbooks without relying on Microsoft Excel. It provides comprehensive Excel operations such as editing sheets, managing data, generating charts, and working with pivot tables through various transport protocols including stdio and HTTP. The server supports robust data validation, advanced formatting, and seamless integration as both a local tool and remote service. Configuration options for file management and port settings allow for flexible deployment.

  2,795 326 MCP
• 37
  

  Substrate MCP Server

  A Rust-based MCP server for dynamic Substrate blockchain operations.

  Substrate MCP Server provides a Model Context Protocol (MCP) compliant server enabling dynamic interaction with Substrate blockchains. It supports querying balances, pallets, and storage, as well as submitting transactions and accessing block and event data. The server is fully configurable via environment variables and designed for seamless integration with tools such as Cursor, Claude, and development dashboards. Built in Rust, it interfaces with Substrate nodes using the subxt crate.

  11 4 MCP
• 38
  

  Box MCP Server (Remote)

  Securely connect AI agents to Box content and Box AI using the Model Context Protocol.

  Box MCP Server (Remote) enables AI agent platforms to securely interact with Box data and AI-powered tools via the Model Context Protocol. It supports OAuth-based authentication and provides various capabilities, including user identification, file and folder operations, and access to Box AI tools. The service exposes an endpoint for easy integration by MCP-compatible clients while ensuring data never leaves the Box environment. It offers both admin console and developer console setup options and comprehensive documentation for connection.

  0 3 MCP
• 39
  

  Jupyter MCP Server

  Real-time, context-aware MCP server for managing and interacting with Jupyter Notebooks.

  Jupyter MCP Server is an implementation of the Model Context Protocol (MCP) designed to enable AI-driven, real-time management and interaction with Jupyter Notebooks. It offers context-aware capabilities, smart execution features, and multimodal output handling, seamlessly integrating with JupyterLab and supporting multiple notebooks simultaneously. The server is compatible with any MCP client and can work with local or hosted Jupyter deployments.

  765 127 MCP
• 40
  

  Netwrix Access Analyzer MCP Server

  An MCP server integrating enterprise access analysis tools with Claude Desktop.

  Netwrix Access Analyzer MCP Server provides a Model Context Protocol (MCP) server designed for integration with Claude Desktop. It enables secure and dynamic access to Active Directory, SQL Server databases, and file system data for auditing and analysis. The server offers a range of tools for effective group membership discovery, permission analysis, sensitive data detection, and more. It streamlines enterprise security assessments by standardizing context-sharing for AI-driven solutions.

  1 1 MCP
• 41
  

  Zaturn

  Your Co-Pilot For Data Analytics & Business Insights

  Zaturn enables AI models to interact with multiple data sources and generate analytics without requiring users to write SQL or Python code. It supports SQL databases and file formats, providing visual and tabular summaries and offering an interactive web interface similar to Jupyter Notebook. Zaturn can function both as a standalone platform or as a Model Context Protocol (MCP) compliant tool, allowing seamless context management for AI-driven data analysis.

  66 9 MCP
• 42
  

  GrowthBook MCP Server

  Interact with GrowthBook from your LLM client via MCP.

  GrowthBook MCP Server enables seamless integration between GrowthBook and LLM clients by implementing the Model Context Protocol. It allows users to view experiment details, add feature flags, and manage GrowthBook configurations directly from AI applications. The server is configurable via environment variables and leverages GrowthBook's API for functionality. This integration streamlines experimentation and feature management workflows in AI tools.

  15 12 MCP
• 43
  

  GitHub GraphQL MCP Server

  A Model Context Protocol server for executing arbitrary GraphQL queries on GitHub's API.

  GitHub GraphQL MCP Server is a Model Context Protocol (MCP) server that enables interaction with GitHub's GraphQL API. It allows users to execute any GraphQL queries and mutations against GitHub, supporting variable injection and error handling. The server is designed to integrate with Claude for Desktop, providing tooling for AI environments to access or manipulate GitHub data. Detailed documentation and configuration examples are provided for rapid setup and use.

  9 4 MCP
• 44
  

  VideoDB Agent Toolkit

  AI Agent toolkit that exposes VideoDB context to LLMs with MCP support

  VideoDB Agent Toolkit provides tools for exposing VideoDB context to large language models (LLMs) and agents, enabling integration with AI-driven IDEs and chat agents. It automates context generation, metadata management, and discoverability by offering structured context files like llms.txt and llms-full.txt, and standardized access via the Model Context Protocol (MCP). The toolkit ensures synchronization of SDK versions, comprehensive documentation, and best practices for seamless AI-powered workflows.

  43 8 MCP
• 45
  

  MCP System Monitor

  Real-time system metrics for LLMs via Model Context Protocol

  MCP System Monitor exposes real-time system metrics, such as CPU, memory, disk, network, host, and process information, through an interface compatible with the Model Context Protocol (MCP). The tool enables language models to retrieve detailed system data in a standardized way. It supports querying various hardware and OS statistics via structured tools and parameters. Designed with LLM integration in mind, it facilitates context-aware system monitoring for AI-driven applications.

  73 17 MCP
• 46
  

  GeoServer MCP Server

  Connect LLMs to GeoServer for geospatial data management and AI-driven queries.

  GeoServer MCP Server implements the Model Context Protocol, enabling seamless integration between Large Language Models (LLMs) and the GeoServer REST API. It allows AI assistants to interact with, query, and manipulate geospatial data and services through standardized interfaces. The server supports management of workspaces, layers, and spatial queries, as well as rendering geospatial visualizations. Installation is supported via Docker, pip, and integration tools like Smithery, with compatibility for clients such as Claude Desktop and Cursor.

  43 9 MCP
• 47
  

  Parallel Task MCP

  Launch deep research or task groups for Parallel APIs via the Model Context Protocol.

  Parallel Task MCP provides a way to initiate and manage research or task groups through LLM clients using the Model Context Protocol. It enables seamless integration with Parallel’s APIs for flexible experimentation and production development. The tool supports both remote and local deployment, and offers connection capabilities for context-aware AI workflows.

  4 3 MCP
• 48
  

  HarmonyOS MCP Server

  Enables HarmonyOS device manipulation via the Model Context Protocol.

  HarmonyOS MCP Server provides an MCP-compatible server that allows programmatic control of HarmonyOS devices. It integrates with tools and frameworks such as OpenAI's openai-agents SDK and LangGraph to facilitate LLM-powered automation workflows. The server supports execution through standard interfaces and can be used with agent platforms to process natural language instructions for device actions. Its design allows for seamless interaction with HarmonyOS systems using the Model Context Protocol.

  25 8 MCP
• 49
  

  Qlik MCP Server

  Connect Claude AI to Qlik Cloud applications and extract insights via the Model Context Protocol.

  Qlik MCP Server enables integration between Claude AI and Qlik Cloud applications through the Model Context Protocol (MCP). It exposes API tools for listing Qlik apps, retrieving sheets and charts, and extracting chart data programmatically. The server supports deployment via Docker, Deno, or Node.js, and can be configured for use with tools like Claude Desktop and Cursor. The setup emphasizes secure handling of Qlik Cloud credentials and flexible environment configuration.

  7 5 MCP
• 50
  

  Aviationstack MCP Server

  MCP server offering comprehensive endpoints for aviation and flight data.

  Aviationstack MCP Server provides an MCP-compliant API that exposes tools to access real-time and scheduled flight data, aircraft details, random aircraft types, countries, and city information from the AviationStack API. It offers ready-to-use endpoints for airline-specific flight queries, airport schedules, and in-depth vehicle, country, and city data. The solution applies the Model Context Protocol by defining MCP tools as Python functions with standardized interfaces, designed for seamless integration into MCP-compatible environments. The server is built using Python, incorporates the FastMCP library, and is intended for easy deployment and use in application development.

  11 4 MCP