Insforge MCP Server - Alternatives & Competitors
A Model Context Protocol server for seamless integration with Insforge and compatible AI clients.
Insforge MCP Server implements the Model Context Protocol (MCP), enabling smooth integration with various AI tools and clients. It allows users to configure and manage connections to the Insforge platform, providing automated and manual installation methods. The server supports multiple AI clients such as Claude Code, Cursor, Windsurf, Cline, Roo Code, and Trae via standardized context management. Documentation and configuration guidelines are available for further customization and usage.
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MyMCP Server (All-in-One Model Context Protocol)
Powerful and extensible Model Context Protocol server with developer and productivity integrations.
MyMCP Server is a robust Model Context Protocol (MCP) server implementation that integrates with services like GitLab, Jira, Confluence, YouTube, Google Workspace, and more. It provides AI-powered search, contextual tool execution, and workflow automation for development and productivity tasks. The system supports extensive configuration and enables selective activation of grouped toolsets for various environments. Installation and deployment are streamlined, with both automated and manual setup options available.
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Vectorize MCP Server
MCP server for advanced vector retrieval and text extraction with Vectorize integration.
Vectorize MCP Server is an implementation of the Model Context Protocol (MCP) that integrates with the Vectorize platform to enable advanced vector retrieval and text extraction. It supports seamless installation and integration within development environments such as VS Code. The server is configurable through environment variables or JSON configuration files and is suitable for use in collaborative and individual workflows requiring vector-based context management for models.
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Agentset MCP
Open-source MCP server for Retrieval-Augmented Generation (RAG) document applications.
Agentset MCP provides a Model Context Protocol (MCP) server designed to power context-aware, document-based applications using Retrieval-Augmented Generation. It enables developers to rapidly integrate intelligent context retrieval into their workflows and supports integration with AI platforms such as Claude. The server is easily installable via major JavaScript package managers and supports environment configuration for namespaces, tenant IDs, and tool descriptions.
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Pica MCP Server
A Model Context Protocol (MCP) server for seamless integration with 100+ platforms via Pica.
Pica MCP Server provides a standardized Model Context Protocol (MCP) interface for interaction with a wide range of third-party services through Pica. It enables direct platform integrations, action execution, and intelligent intent detection while prioritizing secure environment variable management. The server also offers features such as code generation, form and data handling, and robust documentation for platform actions. It supports multiple deployment methods, including standalone, Docker, Vercel, and integration with tools like Claude Desktop and Cursor.
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PostHog MCP
Easily deploy and manage Model Context Protocol servers across multiple platforms.
PostHog MCP provides a server implementation for the Model Context Protocol, now maintained within the PostHog monorepo. It enables quick deployment for enhanced model context management across editors like Cursor, Claude, Claude Code, VS Code, and Zed. Users can install the MCP server with a single command, streamlining integration for large language model workflows. Documentation and further details are provided through official PostHog resources.
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mcp-get
A command-line tool for discovering, installing, and managing Model Context Protocol servers.
mcp-get is a CLI tool designed to help users discover, install, and manage Model Context Protocol (MCP) servers. It enables seamless integration of Large Language Models (LLMs) with various external data sources and tools by utilizing a standardized protocol. The tool provides access to a curated registry of MCP servers and supports installation and management across multiple programming languages and environments. Although now archived, mcp-get simplifies environment variable management, package versioning, and server updates to enhance the LLM ecosystem.
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Taskade MCP
Tools and server for Model Context Protocol workflows and agent integration
Taskade MCP provides an official server and tools to implement and interact with the Model Context Protocol (MCP), enabling seamless connectivity between Taskade’s API and MCP-compatible clients such as Claude or Cursor. It includes utilities for generating MCP tools from any OpenAPI schema and supports the deployment of autonomous agents, workflow automation, and real-time collaboration. The platform promotes extensibility by supporting integration via API, OpenAPI, and MCP, making it easier to build and connect agentic systems.
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CipherTrust Manager MCP Server
Enables AI assistants to access CipherTrust Manager securely via the Model Context Protocol.
CipherTrust Manager MCP Server provides an implementation of the Model Context Protocol (MCP), offering AI assistants such as Claude and Cursor a unified interface to interact with CipherTrust Manager resources. Communication is facilitated through JSON-RPC over stdin/stdout, enabling key management, CTE client management, user management, and connection management functionalities. The tool is configurable via environment variables and integrates with existing CipherTrust Manager instances using the ksctl CLI for secure resource access.
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Stape MCP Server
An MCP server implementation for integrating Stape with AI model context protocols.
Stape MCP Server provides an implementation of the Model Context Protocol server tailored for the Stape platform. It enables secure and standardized access to model context capabilities, allowing integration with tools such as Claude Desktop and Cursor AI. Users can easily configure and authenticate MCP connections using provided configuration samples, while managing context and credentials securely. The server is open source and maintained by the Stape Team under the Apache 2.0 license.
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Codex MCP Server
An MCP-compatible server delivering enriched blockchain data for AI models.
Codex MCP Server implements the Model Context Protocol to provide enriched blockchain data from Codex. It is compatible with MCP clients such as Claude Desktop and Claude CLI, allowing seamless integration in AI workflows that require blockchain context. Users can run the server locally or via npx, and configure it for various MCP-compatible tools using their Codex API key.
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Kanboard MCP Server
MCP server for seamless AI integration with Kanboard project management.
Kanboard MCP Server is a Go-based server implementing the Model Context Protocol (MCP) for integrating AI assistants with the Kanboard project management system. It enables users to manage projects, tasks, users, and workflows in Kanboard directly via natural language commands through compatible AI tools. With built-in support for secure authentication and high performance, it facilitates streamlined project operations between Kanboard and AI-powered clients like Cursor or Claude Desktop. The server is configurable and designed for compatibility with MCP standards.
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Offorte MCP Server
Bridge AI agents with Offorte proposal automation via the Model Context Protocol.
Offorte MCP Server enables external AI models to create and send proposals through Offorte by implementing the Model Context Protocol. It facilitates automation workflows between AI agents and Offorte's proposal engine, supporting seamless integration with chat interfaces and autonomous systems. The server provides a suite of tools for managing contacts, proposals, templates, and automation sets, streamlining the proposal creation and delivery process via standardized context handling. Designed for extensibility and real-world automation, it leverages Offorte's public API to empower intelligent business proposals.
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MCP Server for TheHive
Connect AI-powered automation tools to TheHive incident response platform via MCP.
MCP Server for TheHive enables AI models and automation clients to interact with TheHive incident response platform using the Model Context Protocol. It provides tools to retrieve and analyze security alerts, manage cases, and automate incident response operations. The server facilitates seamless integration by exposing these functionalities over the standardized MCP protocol through stdio communication. It offers both pre-compiled binaries and a source build option with flexible configuration for connecting to TheHive instances.
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Intruder MCP
Enable AI agents to control Intruder.io via the Model Context Protocol.
Intruder MCP allows AI model clients such as Claude and Cursor to interactively control the Intruder vulnerability scanner through the Model Context Protocol. It can be deployed using smithery, locally with Python, or in a Docker container, requiring only an Intruder API key for secure access. The tool provides integration instructions tailored for MCP-compatible clients, streamlining vulnerability management automation for AI-driven workflows.
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QuantConnect MCP Server
Official bridge for secure AI access to QuantConnect's algorithmic trading cloud platform
QuantConnect MCP Server enables artificial intelligence systems such as Claude and OpenAI to interface with QuantConnect's cloud platform through an official, secure, and dockerized implementation of the Model Context Protocol (MCP). It facilitates automated project management, strategy writing, backtesting, and live deployment by exposing a comprehensive suite of API tools for users with valid access credentials. As the maintained official version, it ensures security, easy deployment, and cross-platform compatibility for advanced algorithmic trading automation.
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Lara Translate MCP Server
Context-aware translation server implementing the Model Context Protocol.
Lara Translate MCP Server enables AI applications to seamlessly access professional translation services via the standardized Model Context Protocol. It supports features such as language detection, context-aware translations, and translation memory integration. The server acts as a secure bridge between AI models and Lara Translate, managing credentials and facilitating structured translation requests and responses.
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Unichat MCP Server
Universal MCP server providing context-aware AI chat and code tools across major model vendors.
Unichat MCP Server enables sending standardized requests to leading AI model vendors, including OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, and Inception, utilizing the Model Context Protocol. It features unified endpoints for chat interactions and provides specialized tools for code review, documentation generation, code explanation, and programmatic code reworking. The server is designed for seamless integration with platforms like Claude Desktop and installation via Smithery. Vendor API keys are required for secure access to supported providers.
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mcp-installer
Automated installer for MCP servers across multiple languages.
mcp-installer provides a server that automates the installation of other Model Context Protocol (MCP) servers. It supports installation of MCP servers hosted on npm and PyPi by leveraging tools like npx and uv. The tool is designed to integrate with AI assistants like Claude, enabling users to request remote installations of MCP servers with custom arguments and environment configurations. Its primary goal is to simplify the deployment and management of MCP-compliant servers for various workflows.
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Make MCP Server (legacy)
Enable AI assistants to utilize Make automation workflows as callable tools.
Make MCP Server (legacy) provides a Model Context Protocol (MCP) server that connects AI assistants with Make scenarios configured for on-demand execution. It parses and exposes scenario parameters, allowing AI systems to invoke automation workflows and receive structured JSON outputs. The server supports secure integration through API keys and facilitates seamless communication between AI and Make's automation platform.
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Weblate MCP Server
Seamlessly connect AI assistants to Weblate for translation management via the Model Context Protocol.
Weblate MCP Server enables AI assistants and clients to directly manage Weblate translation projects through the Model Context Protocol (MCP). It integrates with the Weblate REST API, allowing natural language interaction for project and translation management. The tool offers multiple transport options including HTTP, SSE, and STDIO, and is optimized for large language model workflows. Full support for project, component, and translation operations is provided, with a focus on type safety and flexible environment configuration.
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MCP Language Server
Bridge codebase navigation tools to AI models using MCP-enabled language servers.
MCP Language Server implements the Model Context Protocol, allowing MCP-enabled clients, such as LLMs, to interact with language servers for codebase navigation. It exposes standard language server features—like go to definition, references, rename, and diagnostics—over MCP for seamless integration with AI tooling. The server supports multiple languages by serving as a proxy to underlying language servers, including gopls, rust-analyzer, and pyright.
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Godot MCP
A Model Context Protocol (MCP) server implementation using Godot and Node.js.
Godot MCP implements the Model Context Protocol (MCP) as a server, leveraging the Godot game engine along with Node.js and TypeScript technologies. Designed for seamless integration and efficient context management, it aims to facilitate standardized communication between AI models and applications. This project offers a ready-to-use MCP server for developers utilizing Godot and modern JavaScript stacks.
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OpsLevel MCP Server
Read-only MCP server for integrating OpsLevel data with AI tools.
OpsLevel MCP Server implements the Model Context Protocol to provide AI tools with a secure way to access and interact with OpsLevel account data. It supports read-only operations for a wide range of OpsLevel resources such as actions, campaigns, checks, components, documentation, domains, and more. The tool is compatible with popular environments including Claude Desktop and VS Code, enabling easy integration via configuration and API tokens. Installation options include Homebrew, Docker, and standalone binaries.
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Semgrep MCP Server
A Model Context Protocol server powered by Semgrep for seamless code analysis integration.
Semgrep MCP Server implements the Model Context Protocol (MCP) to enable efficient and standardized communication for code analysis tasks. It facilitates integration with platforms like LM Studio, Cursor, and Visual Studio Code, providing both Docker and Python (PyPI) deployment options. The tool is now maintained in the main Semgrep repository with continued updates, enhancing compatibility and support across developer tools.
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Keycloak MCP Server
MCP server for streamlined Keycloak administration and user management
Keycloak MCP Server provides a Model Context Protocol (MCP) interface for managing Keycloak users and realms. It enables easy creation, deletion, and listing of users and realms through standardized tools. Designed for integration with platforms like Claude Desktop and tools like Smithery, it automates repeated Keycloak admin tasks and supports both NPM and local development setups.
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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.
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YAMCP
Unified management and orchestration of Model Context Protocol servers via a local gateway workspace.
YAMCP is a command-line tool that enables organizing and managing multiple MCP (Model Context Protocol) servers as unified workspaces. It allows users to connect to various local or remote MCP servers, group them by functionality or application, and expose them as a single MCP server gateway for AI applications. The tool simplifies monitoring and debugging by centralizing server communication logs and provides workspace management and runtime control. YAMCP facilitates seamless integration with AI applications by providing a consolidated configuration and context management interface.
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Remote-MCP
A type-safe, bidirectional system for remote Model Context Protocol communication.
Remote-MCP provides a simple and secure way to enable remote access to and centralized management of model contexts using the Model Context Protocol. It bridges local MCP clients with remote MCP servers, supporting a modular architecture via tRPC over HTTP. The tool allows integration both as a client and a server, catering to real-time remote access needs ahead of the official MCP roadmap.
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GameBrain MCP API Clients
Easily connect to the GameBrain MCP server with customizable client configuration.
GameBrain MCP API Clients enables users to seamlessly integrate with the GameBrain Model Context Protocol (MCP) server by providing a ready-to-use configuration and client setup. Users can generate a free API key and connect to the server with minimal setup using the supplied JSON config. The tool is designed to facilitate standardized access and communication with remote model context providers.
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SpaceBridge-MCP
A Model Context Protocol server for seamless AI-assisted issue management via SpaceBridge.
SpaceBridge-MCP offers a Model Context Protocol (MCP) server that enables AI assistants and coding tools to interact directly with the SpaceBridge issue aggregation platform. It supports searching, creating, viewing, and updating issues across multiple trackers such as Jira and GitHub, using natural language requests. It also provides automated duplicate detection with LLM-based comparison to streamline issue creation workflows. The server acts as a bridge between AI-powered development environments and issue management systems, enhancing context sharing and productivity.
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Klavis
One MCP server for AI agents to handle thousands of tools.
Klavis provides an MCP (Model Context Protocol) server with over 100 prebuilt integrations for AI agents, enabling seamless connectivity with various tools and services. It offers both cloud-hosted and self-hosted deployment options and includes out-of-the-box OAuth support for secure authentication. Klavis is designed to act as an intelligent connector, streamlining workflow automation and enhancing agent capability through standardized context management.
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kibitz
The coding agent for professionals with MCP integration.
kibitz is a coding agent that supports advanced AI collaboration by enabling seamless integration with Model Context Protocol (MCP) servers via WebSockets. It allows users to configure Anthropic API keys, system prompts, and custom context providers for each project, enhancing contextual understanding for coding tasks. The platform is designed for developers and professionals seeking tailored AI-driven coding workflows and provides flexible project-specific configuration.
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GitHub MCP Server
Connect AI tools directly to GitHub for repository, issue, and workflow management via natural language.
GitHub MCP Server enables AI tools such as agents, assistants, and chatbots to interact natively with the GitHub platform. It allows these tools to access repositories, analyze code, manage issues and pull requests, and automate workflows using the Model Context Protocol (MCP). The server supports integration with multiple hosts, including VS Code and other popular IDEs, and can operate both remotely and locally. Built for developers seeking to enhance AI-powered development workflows through seamless GitHub context access.
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Authenticator App MCP Server
Secure MCP server for AI-assisted access to 2FA codes and passwords.
Authenticator App MCP Server provides a secure Model Context Protocol (MCP) server enabling AI agents to interact with authentication credentials, such as 2FA codes and passwords. It facilitates automated login processes for AI assistants while maintaining robust security by requiring access tokens and integrating with the Authenticator App desktop client. This solution streamlines the management of user credentials across multiple platforms and websites, ensuring seamless and secure credential retrieval by AI agents.
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Exa MCP Server
Fast, efficient web and code context for AI coding assistants.
Exa MCP Server provides a Model Context Protocol (MCP) server interface that connects AI assistants to Exa AI’s powerful search capabilities, including code, documentation, and web search. It enables coding agents to retrieve precise, token-efficient context from billions of sources such as GitHub, StackOverflow, and documentation sites, reducing hallucinations in coding agents. The platform supports integration with popular tools like Cursor, Claude, and VS Code through standardized MCP configuration, offering configurable access to various research and code-related tools via HTTP.
3,224 244 MCP -
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Maven Tools MCP Server
Universal Maven Central dependency intelligence server for JVM build tools via the Model Context Protocol.
Maven Tools MCP Server provides an MCP-compliant API delivering rich Maven Central dependency intelligence for JVM build tools like Maven, Gradle, SBT, and Mill. It enables AI assistants to instantly analyze, interpret, and recommend updates, health checks, and maintenance insights by reading maven-metadata.xml directly from Maven Central. With Context7 integration, it supports orchestration and documentation, enabling bulk analysis, stable version filtering, risk assessment, and rapid cached responses. Designed for seamless integration into AI workflows via the Model Context Protocol.
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Plane MCP Server
Enables LLMs to manage Plane.so projects and issues via the Model Context Protocol.
Plane MCP Server provides a standardized interface to connect large language models with Plane.so project management APIs. It enables LLMs to interact directly with project and issue data, supporting tasks such as listing projects, retrieving detailed information, creating and updating issues, while prioritizing user control and security. Installation is streamlined through tools like Smithery, and configuration supports multiple clients including Claude for Desktop.
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ServeMyAPI
Securely manage and serve API keys via macOS Keychain with an MCP interface
ServeMyAPI is a personal Model Context Protocol (MCP) server designed for macOS, enabling secure storage and access of API keys via the macOS Keychain. It provides both CLI and server interfaces for managing keys and supports stdio and HTTP/SSE transports for seamless integration with various clients. The tool allows natural language interaction and centralized, cross-project key management, aiming to improve developer workflows and AI assistant collaborations. ServeMyAPI eliminates common issues with environment files by offering secure, visible, and AI-accessible key storage.
23 5 MCP -
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Webvizio MCP Server
Bridge between Webvizio feedback and AI coding agents via the Model Context Protocol
Webvizio MCP Server is a TypeScript-based server implementing the Model Context Protocol to securely and efficiently interface with the Webvizio API. It transforms web page feedback and bug reports into structured, actionable developer tasks, providing AI coding agents with comprehensive task context and data. It offers methods to fetch project and task details, retrieve logs and screenshots, and manage task statuses. The server standardizes communication between Webvizio and AI agent clients, facilitating automated issue resolution.
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AtomGit MCP Server
AI-powered management and automation of AtomGit repositories via the Model Context Protocol.
AtomGit MCP Server implements the Model Context Protocol to enable AI-driven management and automation of AtomGit open collaboration platform repositories. It offers methods for managing repositories, issues, pull requests, branches, and labels, allowing seamless AI interaction with AtomGit. The server supports integration with platforms like Claude and VSCode, providing a standardized interface for AI to orchestrate complex collaboration workflows. Built with Node.js and easily deployable via npx or from source, it focuses on expanding collaborative capabilities using AI agents.
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Azure MCP Server
Connect AI agents with Azure services through Model Context Protocol.
Azure MCP Server provides a seamless interface between AI agents and Azure services by implementing the Model Context Protocol (MCP) specification. It enables integration with tools like GitHub Copilot for Azure and supports a wide range of Azure resource management tasks directly via conversational AI interfaces. Designed for extensibility and compatibility, it offers enhanced contextual capabilities for agents working with Azure environments.
1,178 351 MCP -
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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.
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Mifos MCP - Model Context Protocol (MCP)
Enabling AI agents to access and operate on financial data in the Mifos X ecosystem using Model Context Protocol.
Mifos MCP provides a Model Context Protocol (MCP) interface tailored for the Mifos X ecosystem, empowering AI agents to interact with financial data and perform operations within the platform. It offers a Java (Quarkus) implementation, with easy configurability via environment variables and native executable support. Developers can test and debug deployments with the MCP Inspector, and detailed instructions ensure smooth setup and integration. Comprehensive examples demonstrate practical banking and financial automation workflows.
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MCP Atlassian
AI-powered MCP server integrating Confluence and Jira workflows.
MCP Atlassian serves as a Model Context Protocol (MCP) server interface for Atlassian products such as Confluence and Jira, supporting both cloud and server/data center deployments. It enables AI assistants to access, search, and update Atlassian data contextually via standardized MCP endpoints. The integration streamlines tasks like intelligent issue filtering, documentation creation, and context-driven updates directly through natural language. Multiple authentication modes, including API tokens and OAuth 2.0, are supported for secure connectivity.
3,574 740 MCP -
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AgentQL MCP Server
MCP-compliant server for structured web data extraction using AgentQL.
AgentQL MCP Server acts as a Model Context Protocol (MCP) server that leverages AgentQL's data extraction capabilities to fetch structured information from web pages. It allows integration with applications supporting MCP, such as Claude Desktop, VS Code, and Cursor, by providing an accessible interface for extracting structured data based on user-defined prompts. With configurable API key support and streamlined installation, it simplifies the process of connecting web data extraction workflows to AI tools.
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Meta Ads MCP
AI-powered Meta Ads campaign analysis and management via MCP
Meta Ads MCP is a Model Context Protocol (MCP) server for managing, analyzing, and optimizing Meta advertising campaigns. It enables AI interfaces, such as LLMs, to retrieve ad performance data, visualize creatives, and provide strategic insights across Facebook, Instagram, and related platforms. The solution supports integration with platforms like Claude and Cursor, leveraging Meta's public APIs to deliver actionable insights and campaign management capabilities. Authentication options include interactive login and token-based flows for various MCP clients.
342 86 MCP -
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mcp-cli
A command-line inspector and client for the Model Context Protocol
mcp-cli is a command-line interface tool designed to interact with Model Context Protocol (MCP) servers. It allows users to run and connect to MCP servers from various sources, inspect available tools, resources, and prompts, and execute commands non-interactively or interactively. The tool supports OAuth for various server types, making integration and automation seamless for developers working with MCP-compliant servers.
391 31 MCP -
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OpenAI MCP Server
Bridge between Claude and OpenAI models using the MCP protocol.
OpenAI MCP Server enables direct querying of OpenAI language models from Claude via the Model Context Protocol (MCP). It provides a configurable Python server that exposes OpenAI APIs as MCP endpoints. The server is designed for seamless integration, requiring simple configuration updates and environment variable setup. Automated testing is supported to verify connectivity and response from the OpenAI API.
77 19 MCP -
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MCP Linear
MCP server for AI-driven control of Linear project management.
MCP Linear is a Model Context Protocol (MCP) server implementation that enables AI assistants to interact with the Linear project management platform. It provides a bridge between AI systems and the Linear GraphQL API, allowing the retrieval and management of issues, projects, teams, and more. With MCP Linear, users can create, update, assign, and comment on Linear issues, as well as manage project and team structures directly through AI interfaces. The tool supports seamless integration via Smithery and can be configured for various AI clients like Cursor and Claude Desktop.
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REST CSV MCP Server
Generate a REST-based MCP Server for CSV-backed applications.
REST CSV MCP Server is a tool generated using mcpgen to facilitate the implementation of the Model Context Protocol. It compiles TypeScript files to create a build directory, providing JSON configuration compatible with various MCP clients such as Claude Desktop, Windsurf, and Cursor. The server interacts with CSV data through a REST interface and streamlines integration into MCP environments.
11 3 MCP
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