MCP Servers

Chargebee MCP Server allows AI assistants to: - Access Documentation: Retrieve detailed information and usage guides from Chargebee's documentation. - Generate Code Snippets: Create structured code outlines and sample code for integrating Chargebee's APIs and features. - Search Knowledge Base: Explore Chargebee's knowledge base, including documentation, FAQs, and release notes. This integration facilitates AI-driven development workflows by providing context-aware assistance for Chargebee's services.

DevHub CMS MCP allows AI assistants to: - Manage Businesses: Retrieve a list of all businesses within the DevHub account, including their IDs and names. - Handle Locations: Access detailed information about locations associated with a specific business, such as address, coordinates, and URLs. - Retrieve Hours of Operation: Obtain structured hours of operation for a specific location, supporting different types of hours (e.g., primary, holiday). This integration facilitates AI-driven management and retrieval of business and location data within the DevHub CMS, enhancing content management workflows through natural language commands.

DexPaprika MCP Server allows AI assistants to: - Access Real-Time and Historical Data: Retrieve up-to-date and past information on crypto tokens, DEX trading activity, and liquidity across various blockchains. - Perform Market Analysis: Analyze market trends, token performance, and DeFi analytics through a standardized interface. - Utilize Natural Language Queries: Enable AI assistants to explore data using natural language, facilitating intuitive interactions. - Integrate Seamlessly: Designed for easy integration with AI assistants like Claude, requiring minimal configuration. This integration empowers AI-driven exploration and analysis of cryptocurrency markets, enhancing the capabilities of AI assistants in financial contexts.

gotoHuman MCP Server allows AI assistants to: - Request Human Reviews: Submit AI-generated content or actions for human evaluation via gotoHuman forms. - List Available Forms: Retrieve a list of all review forms available in the user's gotoHuman account. - Fetch Form Schemas: Obtain the schema of specific forms to structure review requests appropriately. - Handle Webhook Responses: Receive asynchronous responses from human reviewers to proceed with or halt AI-driven actions. This integration facilitates human-in-the-loop workflows, ensuring that critical AI-generated decisions are reviewed and approved by humans before execution.

Sketch Context MCP allows AI assistants to: - Parse Sketch Files: Analyze .sketch files to extract design components and layout information. - Provide Design Context: Supply AI coding agents with structured data about Sketch designs to inform code generation. - Reference Specific Elements: Enable referencing of specific components and layers from Sketch files within AI-assisted development workflows. This integration facilitates AI-driven design-to-code workflows by providing structured access to Sketch design data.

MCP ODBC Server allows AI assistants to: - Connect to ODBC-Compatible Databases: Interface with databases like Virtuoso, PostgreSQL, MySQL, Oracle, and more via ODBC drivers. - Execute SQL and SPARQL Queries: Perform standard SQL queries and SPARQL queries, including SPASQL (SPARQL inside SQL). - Retrieve Database Metadata: Access schemas, tables, and detailed table descriptions. - Filter Table Names: Search for tables based on substring patterns. - Integrate with OpenLink AI Layer (OPAL): Utilize stored procedures for passing prompts to supported Large Language Models. This integration enables AI-driven interaction with a wide range of databases, facilitating tasks such as data retrieval and analysis through natural language commands.

DocsMCP allows AI assistants to: - Access Documentation: Retrieve documentation from specified sources, including local files and remote URLs. - Query Content: Perform searches within the documentation to find relevant information. - Integrate Seamlessly: Configure with MCP-compatible clients like Cursor IDE for automatic utilization. This integration facilitates AI-driven access to documentation, enhancing the ability to retrieve and utilize information from various sources.

Jira MCP Server allows AI assistants to: - Retrieve Issue Details: Access detailed information about specific Jira issues. - Search Issues with JQL: Utilize Jira Query Language to find issues matching specific criteria. - Manage Sprints: List and manage active sprints within Jira projects. - Create and Update Issues: Add new issues or modify existing ones. - List Available Statuses: View all possible statuses for issues in Jira. - Transition Issues: Move issues through various workflow states. This integration facilitates AI-driven management of Jira projects, streamlining tasks such as issue tracking and sprint planning through natural language commands.

Raindrop.io MCP Server allows AI assistants to: - Add Bookmarks: Save new bookmarks to Raindrop.io with specified tags. - Fetch Latest Bookmarks: Retrieve the most recently added bookmarks. - Search Bookmarks by Tag: Find bookmarks associated with specific tags. - Search Bookmarks by Query: Perform text-based searches across bookmarks.

CUA MCP Server allows AI assistants to: - Interact with Virtual Environments: Control and automate tasks within isolated macOS and Linux virtual machines. - Execute Complex Workflows: Perform multi-step operations involving various applications and system commands. - Enhance Security: Operate within sandboxed environments to ensure system integrity. This integration facilitates AI-driven automation and interaction with desktop applications through natural language commands.

A Node.js server implementing Model Context Protocol (MCP) for Webflow using the Webflow JavaScript SDK. Enable AI Clients to interact with the Webflow APIs through the Model Context Protocol (MCP). Learn more about Webflow's APIs in the developer documentation.

Documentation for Velt SDK. Velt provides ready-made enterprise grade collaboration features like Comments, Notifications, Recording, Live Editing etc.

Documentation for Velt SDK. Velt provides ready-made enterprise grade collaboration features like Comments, Notifications, Recording, Live Editing etc.

Rootly MCP Server allows AI assistants to: - Manage Incidents: Create, list, and retrieve details of incidents. - Access Incident Alerts: Retrieve alerts associated with specific incidents. This integration facilitates AI-driven incident management, enabling users to handle production incidents efficiently without leaving their integrated development environments.

Zapier MCP (Model Context Protocol) is a service that enables AI assistants to interact with over 7,000 applications and perform more than 30,000 actions without the need for complex API integrations. This allows AI models to execute tasks such as sending messages, managing data, scheduling events, and updating records, thereby transforming them from mere conversational tools into functional extensions of various applications.

Redshift MCP Server allows AI assistants to: - Inspect Database Schemas: Access and navigate schemas, tables, and columns within an Amazon Redshift data warehouse. - Execute Read-Only Queries: Perform SQL queries to retrieve data without modifying the database. - Retrieve Table Structures: Obtain detailed information about specific tables, including column names and data types. - Find Columns Across Tables: Identify tables containing columns that match specific patterns or names. This integration enables AI-driven exploration and querying of Redshift databases through natural language commands.

EdgeOne Pages MCP allows AI assistants to: - Deploy HTML Content: Send HTML content to EdgeOne Pages and receive a publicly accessible URL. - Automate Content Hosting: Utilize EdgeOne Pages' infrastructure for rapid content delivery. This integration facilitates AI-driven deployment of web content, streamlining the process of hosting and sharing HTML pages.

Mobile MCP Server allows AI assistants to: - Automate Native Apps: Interact with iOS and Android applications using accessibility snapshots or coordinate-based taps. - Perform Scripted Flows: Execute multi-step user journeys without manual control of simulators or physical devices. - Extract Structured Data: Retrieve structured data from on-screen elements. - Manage App Lifecycle: Launch, terminate, and manage applications on devices. This integration enables AI-driven mobile automation, supporting tasks such as testing, data entry, and general-purpose application interaction through natural language commands.