MCP Simple Timeserver - Alternatives & Competitors
Provides local and UTC time to AI models via the Model Context Protocol.
MCP Simple Timeserver provides current local time, timezone, and UTC information to AI models such as Claude by serving as a Model Context Protocol (MCP) tool. It offers two main endpoints: one for retrieving the user's local time and timezone, and another for fetching the current UTC time from an NTP server. The project supports both local and web server deployments and can be integrated into the Claude desktop app to enhance temporal awareness for LLMs.
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mcp-time
A Model Context Protocol server for time and date operations
mcp-time is a Model Context Protocol (MCP) server that enables AI assistants and MCP clients to perform standardized time and date-related operations. It provides natural language parsing for relative time expressions, supports flexible formatting, and allows manipulation and comparison of times. The server offers multiple integration methods, including stdio, HTTP stream, Docker, and npx for compatibility with various clients. It is designed for robust time handling and easy integration with AI tools.
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mcp-datetime
Datetime formatting service MCP server for Claude Desktop App
mcp-datetime provides a datetime formatting service implemented as an MCP server for integration with the Claude Desktop Application. It offers generation of current date and time strings in various formats, including standard, Japanese, ISO, and filename-friendly outputs. The server exposes a 'get_datetime' tool for easy retrieval of formatted dates and times with support for timezone handling and multi-language output. Seamless integration and Python packaging facilitate installation and extensibility.
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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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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.
93 9 MCP -
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Climatiq MCP Server
MCP server providing AI assistants with real-time carbon emissions calculations via Climatiq API.
Climatiq MCP Server implements the Model Context Protocol to bridge AI assistants with the Climatiq API for precise carbon emissions calculations. It exposes a set of tools for various emissions scenarios, including electricity use, travel, freight, and more. The server generates resource URIs for detailed emission reports and provides natural language explanations on climate impact. Configuration is streamlined via environment variables, CLI tools, or files, supporting easy integration with platforms like Claude Desktop.
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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.
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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.
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Calculator MCP Server
Enables LLMs to perform precise numerical calculations via Model Context Protocol.
Calculator MCP Server provides a Model Context Protocol-compliant server which allows large language models to use calculator functionality for accurate numerical operations. It offers a single tool called 'calculate' for evaluating mathematical expressions that can be integrated into MCP ecosystems. Installation and configuration options are available via pip or uvx to support multiple client workflows. The server simplifies connecting LLMs to robust, external calculation capabilities for enhanced mathematical reasoning.
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MCP CLI
A powerful CLI for seamless interaction with Model Context Protocol servers and advanced LLMs.
MCP CLI is a modular command-line interface designed for interacting with Model Context Protocol (MCP) servers and managing conversations with large language models. It integrates with the CHUK Tool Processor and CHUK-LLM to provide real-time chat, interactive command shells, and automation capabilities. The system supports a wide array of AI providers and models, advanced tool usage, context management, and performance metrics. Rich output formatting, concurrent tool execution, and flexible configuration make it suitable for both end-users and developers.
1,755 299 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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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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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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MCP-Human
Enabling human-in-the-loop decision making for AI assistants via the Model Context Protocol.
MCP-Human is a server implementing the Model Context Protocol that connects AI assistants with real human input on demand. It creates tasks on Amazon Mechanical Turk, allowing humans to answer questions when AI systems require assistance. This solution demonstrates human-in-the-loop AI by providing a bridge between AI models and external human judgment through a standardized protocol. Designed primarily as a proof-of-concept, it can be easily integrated with MCP-compatible clients.
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TaskWarrior MCP Server
MCP server for managing TaskWarrior tasks via a standardized protocol
Implements the Model Context Protocol (MCP) to provide a Node.js server interface for TaskWarrior operations. Allows viewing, filtering, adding, and completing tasks through a standardized API. Integrates with task management workflows by utilizing the local TaskWarrior client, supporting advanced task attributes like projects and tags. Enables seamless task manipulation for external tools such as Claude Desktop.
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Cal Server
Lightweight mathematical expression calculator as an MCP service
Cal Server is a simple mathematical expression calculation tool built on the FastMCP framework and designed to operate as a Model Context Protocol (MCP) service. It evaluates mathematical expressions provided via standard input/output using the expr-eval library and runs in the Bun runtime environment. The service supports core mathematical operations, built-in constants, and parameter validation with zod, making it efficient and easy to integrate into other workflows.
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MCP-timeserver
A simple MCP server providing date and time information to agentic systems.
MCP-timeserver exposes current datetime information via a custom datetime URI scheme compatible with the Model Context Protocol. It allows agentic systems and chat REPLs to access timezone-aware current times and offers a tool to fetch the system's local time. The server is designed to integrate with MCP-based workflows by providing standardized datetime resources.
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Time Node MCP Server
Timezone-aware date and time operations for AI assistants and applications.
Time Node MCP Server is an implementation of the Model Context Protocol (MCP) designed to provide accurate, timezone-aware date and time operations. It exposes tools for retrieving and converting times across IANA timezones, detecting system timezone, and offering outputs in multiple formats. The server ensures correct handling of Daylight Saving Time transitions and supports integration with AI assistants like Claude Desktop.
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MCP Weather Server
Provides weather forecasts to LLMs via the Model Context Protocol.
MCP Weather Server enables large language models to access real-time, accurate weather forecasts by interfacing with the AccuWeather API. It offers both hourly and daily weather data, supporting metric and imperial units, and can be seamlessly integrated with MCP-compatible clients like Claude Desktop or supergateway. The server provides tools for retrieving weather based on location and settings, with robust configuration options. It is designed for straightforward deployment using Node.js and environment-configured API keys.
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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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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.
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ntfy-me-mcp
Send real-time notifications from AI assistants to your devices using ntfy and the Model Context Protocol.
ntfy-me-mcp implements a streamlined Model Context Protocol (MCP) server, enabling AI assistants to send real-time notifications to user devices through the ntfy service. It supports both public and self-hosted ntfy instances with token authentication, allowing integration into various AI workflows. The server automatically detects URLs for interactive actions and applies smart markdown formatting to craft rich notifications suitable for important events and task updates.
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mcp-server-templates
Deploy Model Context Protocol servers instantly with zero configuration.
MCP Server Templates enables rapid, zero-configuration deployment of production-ready Model Context Protocol (MCP) servers using Docker containers and a comprehensive CLI tool. It provides a library of ready-made templates for common integrations—including filesystems, GitHub, GitLab, and Zendesk—and features intelligent caching, smart tool discovery, and flexible configuration options via JSON, YAML, environment variables, or CLI. Perfect for AI developers, data scientists, and DevOps teams, it streamlines the process of setting up and managing MCP servers and has evolved into the MCP Platform for enhanced capabilities.
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Stadia Maps MCP Server (TypeScript)
Bringing location services, geocoding, and mapping to AI assistants via Stadia Maps APIs.
Stadia Maps MCP Server (TypeScript) implements the Model Context Protocol to provide LLM-based assistants with structured access to Stadia Maps APIs. It enables AI tools to query for geocoding, routing, time zones, map generation, and isochrone calculations. Designed for integration with agentic tools and LLMs, the server enhances spatial intelligence and location-based features in AI workflows.
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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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mcp
Universal remote MCP server connecting AI clients to productivity tools.
WayStation MCP acts as a remote Model Context Protocol (MCP) server, enabling seamless integration between AI clients like Claude or Cursor and a wide range of productivity applications, such as Notion, Monday, Airtable, Jira, and more. It supports multiple secure connection transports and offers both general and user-specific preauthenticated endpoints. The platform emphasizes ease of integration, OAuth2-based authentication, and broad app compatibility. Users can manage their integrations through a user dashboard, simplifying complex workflow automations for AI-powered productivity.
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mcp-server-tidb
MCP server implementation for TiDB serverless databases.
mcp-server-tidb provides an implementation of the Model Context Protocol (MCP) for TiDB, enabling integration with serverless TiDB databases. It supports configuration through environment variables or .env files and connects with applications such as Claude Desktop via standardized configuration. The server facilitates managing context between conversational AI models and a TiDB backend in a consistent and standardized way.
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awslabs/mcp
Specialized MCP servers for seamless AWS integration in AI and development environments.
AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.
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mcp-server-home-assistant
A Model Context Protocol Server integration for Home Assistant.
Provides an MCP server interface for Home Assistant, enabling context sharing between Home Assistant and AI models through the Model Context Protocol. Allows users to connect Claude Desktop and similar tools to Home Assistant via a WebSocket API and secure API token. Facilitates seamless integration by leveraging a custom Home Assistant component that is migrating into Home Assistant Core. Enables access and manipulation of smart home context data in standardized ways.
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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.
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mcpmcp-server
Seamlessly discover, set up, and integrate MCP servers with AI clients.
mcpmcp-server enables users to discover, configure, and connect MCP servers with preferred clients, optimizing AI integration into daily workflows. It supports streamlined setup via JSON configuration, ensuring compatibility with various platforms such as Claude Desktop on macOS. The project simplifies the connection process between AI clients and remote Model Context Protocol servers. Users are directed to an associated homepage for further platform-specific guidance.
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IP Find MCP Server
A Model Context Protocol server for IP location lookups by AI assistants.
IP Find MCP Server acts as a Model Context Protocol (MCP) server, allowing AI assistants to access geolocation data from the IP Find API. It connects the IP Find API with AI tools, enabling the retrieval of IP address location information in standardized contexts. Designed for integration with MCP clients such as the Claude Desktop App, it simplifies configuration and secure API key management. The server is certified by MCPHub.
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MCP Zotero
Model Context Protocol server for seamless Zotero integration with AI tools.
MCP Zotero provides a Model Context Protocol server enabling AI models such as Claude to access and interact with Zotero libraries. Users can securely link their Zotero accounts and perform actions including listing collections, retrieving papers, searching the library, and getting details about specific items. Integration is designed for both standalone operation and as an extension for tools like Claude Desktop.
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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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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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mcp-server
A production-ready Model Context Protocol server for advanced aerospace and astrodynamics calculations.
The mcp-server provides a Model Context Protocol (MCP) server specifically designed for aerospace and astrodynamics computations. It offers both STDIO and HTTP/SSE transport options, enabling seamless integration with MCP clients for tasks like celestial body ephemeris, orbital mechanics, geometry, ground station operations, and time system conversions. Powered by the IO Aerospace Astrodynamics framework, it supports rapid, context-aware scientific tool execution for applications in mission analysis and research. Extensible deployment methods, including Docker and .NET, and a focus on easy client integration are core components.
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Weather MCP Server
A Model Context Protocol server delivering weather and air quality data via multiple transport modes.
Weather MCP Server is a Model Context Protocol (MCP) implementation that provides comprehensive weather and air quality information using the Open-Meteo API. It supports various transport modes including standard stdio for desktop clients, HTTP Server-Sent Events (SSE), and Streamable HTTP for modern web integration. The server offers both real-time and historical weather metrics, as well as timezone and time conversion functionalities. Installation and integration options are available for both MCP desktop clients and web applications.
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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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Macrocosmos MCP
Official Model Context Protocol server for real-time social and video data integration.
Macrocosmos MCP is the official server implementation of the Model Context Protocol (MCP). It connects AI clients with real-time data from platforms like X, Reddit, and YouTube, powered by Data Universe (SN13) on Bittensor. The server enables MCP-compatible clients to fetch social media and video transcript data for enhanced contextual understanding. It supports integration with tools such as Claude Desktop, Cursor, Windsurf, and OpenAI Agents.
24 3 MCP -
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Dappier MCP Server
Real-time web search and premium data access for AI agents via Model Context Protocol.
Dappier MCP Server enables fast, real-time web search and access to premium data sources, including news, financial markets, sports, and weather, for AI agents using the Model Context Protocol (MCP). It integrates seamlessly with tools like Claude Desktop and Cursor, allowing users to enhance their AI workflows with up-to-date, trusted information. Simple installation and configuration are provided for multiple platforms, leveraging API keys for secure access. The solution supports deployment via Smithery and direct installation with 'uv', facilitating rapid setup for developers.
35 11 MCP -
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Flowcore Platform MCP Server
A standardized MCP server for managing and interacting with Flowcore Platform resources.
Flowcore Platform MCP Server provides an implementation of the Model Context Protocol (MCP) for seamless interaction and management of Flowcore resources. It enables AI assistants to query and control the Flowcore Platform using a structured API, allowing for enhanced context handling and data access. The server supports easy deployment with npx, npm, or Bun and requires user authentication using Flowcore credentials.
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TSGram MCP
Bring Claude Code AI to Telegram via local Model Context Protocol server.
TSGram MCP connects Claude Code sessions with Telegram using a local server and Docker, enabling AI-powered code assistance within Telegram chats. It allows users to query, edit, and manage codebases directly from their mobile devices, while keeping all data local for privacy. The setup process is streamlined with support for both AI-guided and CLI-based installation, making integration with existing projects simple. A local web dashboard aids in bot management, ensuring secure and efficient context handling between user code and language models.
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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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MCP Server for Google Tag Manager
Remote MCP server enabling Google Tag Manager integration with AI clients.
MCP Server for Google Tag Manager enables remote MCP connections with built-in Google OAuth, creating an interface to the Google Tag Manager API. It facilitates secure authentication and streamlined access for AI tools like Claude Desktop and Cursor AI. Developers can quickly configure their MCP clients for seamless integration and manage credentials with ease. Tools and workflows become accessible once authenticated, enhancing contextual interaction and automation through Google Tag Manager.
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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.
8 5 MCP -
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MCP-Twikit
A Model Context Protocol server for Twitter search and interaction.
MCP-Twikit is an MCP-compliant server that enables interaction with the Twitter platform via the Model Context Protocol. It supports functions such as searching tweets, analyzing sentiments across accounts, and retrieving a user's Twitter timeline. The tool is designed for integration with AI clients to facilitate structured, context-aware access to Twitter data.
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Coinmarket MCP server
Access CoinMarketCap data through MCP for AI models and tools
Coinmarket MCP Server provides an interface for accessing CoinMarketCap cryptocurrency data via the Model Context Protocol. It supports retrieving the latest currency listings and token quotes using custom URI schemes. The server is compatible with environments like Claude Desktop and Docker, and requires a CoinMarketCap API key for operation.
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OpenMCP
A standard and registry for converting web APIs into MCP servers.
OpenMCP defines a standard for converting various web APIs into servers compatible with the Model Context Protocol (MCP), enabling efficient, token-aware communication with client LLMs. It also provides an open-source registry of compliant servers, allowing clients to access a wide array of external services. The platform supports integration with local and remote hosting environments and offers tools for configuring supported clients, such as Claude desktop and Cursor. Comprehensive guidance is offered for adapting different API formats including REST, gRPC, GraphQL, and more into MCP endpoints.
252 27 MCP -
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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.
138 23 MCP -
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Zettelkasten MCP Server
A Zettelkasten-based knowledge management system implementing the Model Context Protocol.
Zettelkasten MCP Server provides an implementation of the Zettelkasten note-taking methodology, enriched with bidirectional linking, semantic relationships, and categorization of notes. It enables creation, exploration, and synthesis of atomic knowledge using MCP for AI-assisted workflows. The system integrates with clients such as Claude and supports markdown, advanced search, and a structured prompt framework for large language models. The dual storage architecture and synchronous operation model ensure flexibility and reliability for managing personal or collaborative knowledge bases.
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Open Data Model Context Protocol
Easily connect open data providers to LLMs using a Model Context Protocol server and CLI.
Open Data Model Context Protocol enables seamless integration of open public datasets into Large Language Model (LLM) applications, starting with support for Claude. Through a CLI tool and server, users can access and query public data providers within their LLM clients. It also offers tools and templates for contributors to publish and distribute new open datasets, making data discoverable and actionable for LLM queries.
140 21 MCP
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