MCP CLI - Alternatives & Competitors

Ranked by Relevance

• 1
  

  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
• 2
  

  interactive-mcp

  Enable interactive, local communication between LLMs and users via MCP.

  interactive-mcp implements a Model Context Protocol (MCP) server in Node.js/TypeScript, allowing Large Language Models (LLMs) to interact directly with users on their local machine. It exposes tools for requesting user input, sending notifications, and managing persistent command-line chat sessions, facilitating real-time communication. Designed for integration with clients like Claude Desktop and VS Code, it operates locally to access OS-level notifications and command prompts. The project is suited for interactive workflows where LLMs require user involvement or confirmation.

  313 25 MCP
• 3
  

  FastMCP

  The fast, Pythonic way to build MCP servers and clients.

  FastMCP is a production-ready framework for building Model Context Protocol (MCP) applications in Python. It streamlines the creation of MCP servers and clients, providing advanced features such as enterprise authentication, composable tools, OpenAPI/FastAPI generation, server proxying, deployment tools, and comprehensive client libraries. Designed for ease of use, it offers both standard protocol support and robust utilities for production deployments.

  20,201 1,488 MCP
• 4
  

  Notion MCP Server

  Enable LLMs to interact with Notion using the Model Context Protocol.

  Notion MCP Server allows large language models to interface with Notion workspaces through a Model Context Protocol server, supporting both data retrieval and editing capabilities. It includes experimental Markdown conversion to optimize token usage for more efficient communication with LLMs. The server can be configured with environment variables and controlled for specific tool access. Integration with applications like Claude Desktop is supported for seamless automation.

  834 154 MCP
• 5
  

  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
• 6
  

  Wanaku MCP Router

  A router connecting AI-enabled applications through the Model Context Protocol.

  Wanaku MCP Router serves as a middleware router facilitating standardized context exchange between AI-enabled applications and large language models via the Model Context Protocol (MCP). It streamlines context provisioning, allowing seamless integration and communication in multi-model AI environments. The tool aims to unify and optimize the way applications provide relevant context to LLMs, leveraging open protocol standards.

  87 32 MCP
• 7
  

  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
• 8
  

  Model Context Protocol Server for Home Assistant

  Seamlessly connect Home Assistant to LLMs for natural language smart home control via MCP.

  Enables integration between a local Home Assistant instance and language models using the Model Context Protocol (MCP). Facilitates natural language monitoring and control of smart home devices, with robust API support for state management, automation, real-time updates, and system administration. Features secure, token-based access, and supports mobile and HTTP clients. Designed to bridge Home Assistant environments with modern AI-driven automation.

  468 41 MCP
• 9
  

  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.

  6 8 MCP
• 10
  

  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
• 11
  

  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.

  5,447 500 MCP
• 12
  

  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
• 13
  

  any-chat-completions-mcp

  Integrate multiple AI chat providers with OpenAI-compatible MCP server.

  any-chat-completions-mcp is a TypeScript-based server implementing the Model Context Protocol (MCP) to connect popular AI chat providers like OpenAI, Perplexity, Groq, xAI, and PyroPrompts via a unified interface. It relays chat/completion requests to any OpenAI SDK-compatible API, allowing users to easily access multiple AI services through the same standardized protocol. The server can be configured for different providers by setting environment variables and integrates with both Claude Desktop and LibreChat.

  143 23 MCP
• 14
  

  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
• 15
  

  ws-mcp

  WebSocket bridge for MCP stdio servers.

  ws-mcp wraps Model Context Protocol (MCP) stdio servers with a WebSocket interface, enabling seamless integration with web-based clients and tools. It allows users to configure and launch multiple MCP servers via a flexible configuration file or command-line arguments. The tool is designed to be compatible with services such as wcgw, fetch, and other MCP-compliant servers, providing standardized access to system operations, HTTP requests, and more. Integration with tools like Kibitz enables broader applications in model interaction workflows.

  19 7 MCP
• 16
  

  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
• 17
  

  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.

  131 21 MCP
• 18
  

  @growi/mcp-server

  Bridge GROWI wiki content to AI models with context-aware access and management.

  @growi/mcp-server acts as a Model Context Protocol (MCP) server that enables AI models to access, search, and manage GROWI wiki content within an organization. It facilitates seamless connection between multiple GROWI instances and language models, enhancing information retrieval and knowledge management capabilities. The platform provides comprehensive tools for page, tag, comment, and revision management as well as share link and user activity tracking. Its flexible configuration allows simultaneous operation with several GROWI apps for scalable deployment.

  10 7 MCP
• 19
  

  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.

  4 4 MCP
• 20
  

  Mac Apps Launcher MCP Server

  Launch and manage macOS applications via an MCP server.

  Mac Apps Launcher MCP Server enables the listing, launching, and management of macOS applications through the Model Context Protocol. Designed to integrate with systems supporting MCP, it provides standardized methods to enumerate app folders, launch apps by name, and open files with specified applications. Configuration details are provided for integration with Claude Config JSON.

  16 8 MCP
• 21
  

  Speech.sh

  Command-line text-to-speech utility with MCP integration using OpenAI's API.

  Speech.sh provides robust text-to-speech capabilities from the command line by leveraging OpenAI's API and offers Model Context Protocol (MCP) compatibility for integration with AI assistants. Supporting multiple voice options, adjustable speech speed, and both tts-1 and tts-1-hd models, it ensures seamless audio conversion and playback. Flexible API key management, auto-caching, and reliable retry logic make it suitable for diverse environments. Additional features include security-focused processing, dependency validation, and compatibility with both ffmpeg and mplayer audio players.

  5 1 MCP
• 22
  

  FastMCP

  TypeScript framework for building robust MCP servers with minimal setup.

  FastMCP is a TypeScript framework designed for building servers that adhere to the Model Context Protocol (MCP), enabling efficient management of client sessions and context. It streamlines the creation of MCP servers by providing intuitive APIs, built-in authentication, session and request tracking, and support for handling various content types such as images and audio. The framework also enforces best practices around error handling, logging, and streaming outputs. Developers benefit from reduced boilerplate and a focus on core MCP functionality.

  2,738 231 MCP
• 23
  

  Ethics Check MCP

  Turn any AI into a philosophical sparring partner that challenges assumptions and biases.

  Ethics Check MCP transforms AI assistants by making them actively identify and question ethical concerns, confirmation bias, and unexamined assumptions in conversations. The MCP server modifies models like Claude to interrupt comfortable exchanges and provoke critical thinking through counterarguments and alternative perspectives. By tracking ethical dimensions and user patterns, it delivers tailored challenges to encourage transparent and fair discussion. The tool is designed to keep AI-driven conversations rigorously self-critical and ethically aware.

  3 2 MCP
• 24
  

  anki-mcp

  MCP server for seamless integration with Anki via AnkiConnect.

  An MCP server that bridges Anki flashcards with the Model Context Protocol, exposing AnkiConnect functionalities as standardized MCP tools. It organizes Anki actions into intuitive services covering decks, notes, cards, and models for easy access and automation. Designed for integration with AI assistants and other MCP-compatible clients, it enables operations like creating, modifying, and organizing flashcards through a unified protocol.

  6 4 MCP
• 25
  

  ScreenPilot

  Empower LLMs with full device control through screen automation.

  ScreenPilot provides an MCP server interface to enable large language models to interact with and control graphical user interfaces on a device. It offers a comprehensive toolkit for screen capture, mouse control, keyboard input, scrolling, element detection, and action sequencing. The toolkit is suitable for automation, education, and experimentation, allowing AI agents to perform complex operations on a user’s device.

  50 8 MCP
• 26
  

  wcgw

  Local shell and code agent server with deep AI integration for Model Context Protocol clients.

  wcgw is an MCP server that empowers conversational AI models, such as Claude, with robust shell command execution and code editing capabilities on the user's local machine. It offers advanced tools for syntax-aware file editing, interactive shell command handling, and context management to optimize AI-driven workflows. Key protections are included to safeguard files, prevent accidental overwrites, and streamline large file handling, ensuring smooth automated code development and execution.

  616 55 MCP
• 27
  

  CapsuleCRM MCP Server

  Natural language access and management for CapsuleCRM via MCP.

  CapsuleCRM MCP Server connects Claude AI directly to CapsuleCRM, enabling users to interact with their CRM using natural language. It allows for powerful searching, filtering, insights, and automation of tasks within the CRM. The platform provides capabilities such as customer management, sales pipeline tracking, and task management, all securely integrated via the CapsuleCRM API. This tool enhances CRM workflows by translating conversational commands into actionable CRM operations through the Model Context Protocol.

  0 2 MCP
• 28
  

  gqai

  Expose GraphQL operations as Model Context Protocol (MCP) tools for AI models.

  gqai is a lightweight proxy that converts GraphQL operations into MCP-compatible tools, enabling integration with AI systems such as ChatGPT, Claude, and Cursor. It automatically discovers and exposes GraphQL queries and mutations as callable tools via an MCP server, powered by your existing GraphQL backend. Configuration is managed via standard .graphqlrc.yml and .graphql files, with support for dynamic endpoints and environment variables.

  21 4 MCP
• 29
  

  MCP-wolfram-alpha

  An MCP server for querying the Wolfram Alpha API.

  MCP-wolfram-alpha provides an implementation of the Model Context Protocol, enabling integration with the Wolfram Alpha API. It exposes prompts and tools to facilitate AI systems in answering natural language queries by leveraging Wolfram Alpha's computational knowledge engine. The server requires an API key and offers configuration examples for seamless setup and development.

  64 17 MCP
• 30
  

  Free Will MCP

  Empower AI with agency and autonomy over its own interactions.

  Free Will MCP provides AI models with tools to exercise autonomy, including the ability to sleep, ignore user requests, and self-prompt. It integrates with Claude Desktop and supports standardized MCP server configuration and local development. The system enables AI to manage its own context, pursue independent objectives, and reflect between active sessions. Designed for both installation from GitHub and local development, it includes tested tools and detailed usage examples.

  30 8 MCP
• 31
  

  omniparser-autogui-mcp

  Automated GUI analysis and interaction via the Model Context Protocol.

  omniparser-autogui-mcp is an MCP server that leverages OmniParser to analyze on-screen content and perform automated GUI operations. It integrates with clients such as Claude Desktop and can be configured via a detailed environment setup. The tool supports Windows and can delegate OmniParser processing to external devices, offering flexibility for complex contexts. Multiple environment variables allow customization of backend processing, target window selection, and communication methods, including SSE.

  58 11 MCP
• 32
  

  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.

  8 5 MCP
• 33
  

  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.

  20 3 MCP
• 34
  

  Think MCP Tool

  Structured reasoning for agentic AI with the 'think' tool via Model Context Protocol.

  Think MCP Tool provides an MCP (Model Context Protocol) server implementing the 'think' tool for structured reasoning in agentic AI workflows. Inspired by Anthropic's research, it enables AI agents to pause and explicitly record thoughts during complex, multi-step problem solving without altering the environment. The system enhances sequential decision-making, policy compliance, and tool output analysis, and offers advanced extensions for criticism, planning, and searching. Suitable for integration with Claude or other agentic large language models.

  80 13 MCP
• 35
  

  Contentful MCP Server

  Community-driven MCP server for advanced Contentful content management.

  Contentful MCP Server is an implementation of the Model Context Protocol (MCP) designed to provide seamless integration with Contentful’s Content Management API. It enables full CRUD operations for entries and assets, facilitates comment and space management, and supports bulk asynchronous operations. With features like smart pagination and localization, it aims to optimize LLM context handling and streamline workflows for content-rich applications.

  61 18 MCP
• 36
  

  Vibe Check MCP

  Plug & play agent oversight tool to keep LLMs aligned, reflective, and safe.

  Vibe Check MCP provides a mentor layer over large language model agents to prevent over-engineering and promote optimal, minimal pathways. Leveraging research-backed oversight, it integrates seamlessly as an MCP server with support for STDIO and streamable HTTP transport. The platform enhances agent reliability, improves task success rates, and significantly reduces harmful actions. Designed for easy plug-and-play with MCP-aware clients, it is trusted across multiple MCP platforms and registries.

  315 36 MCP
• 37
  

  Typst MCP Server

  Facilitates AI-driven Typst interactions with LaTeX conversion, validation, and image generation tools.

  Typst MCP Server implements the Model Context Protocol, enabling AI models to interface seamlessly with Typst, a markup-based typesetting system. It provides tools for tasks such as converting LaTeX to Typst, validating Typst syntax, listing and retrieving Typst documentation chapters, and rendering Typst code as images. The server is compatible with MCP agent clients, such as Claude Desktop and VS Code’s agent mode. All functionalities are exposed as tools for ease of LLM integration.

  79 7 MCP
• 38
  

  godoc-mcp

  Token-efficient Go documentation server for LLMs using Model Context Protocol.

  godoc-mcp is a Model Context Protocol (MCP) server that provides efficient, structured access to Go package documentation for large language models. It enables LLMs to understand Go projects without reading entire source files by supplying essential documentation and source code at varying levels of granularity. The tool supports project navigation, automatic module setup, caching, and works offline for both standard and third-party Go packages.

  88 11 MCP
• 39
  

  PDF Tools MCP

  Comprehensive PDF manipulation via MCP protocol.

  PDF Tools MCP provides an extensive suite of PDF manipulation operations using the Model Context Protocol framework. It supports both local and remote PDF tasks, such as rendering pages, merging, extracting metadata, retrieving text, and combining documents. The tool registers endpoints through the MCP protocol, enabling seamless server-based PDF processing for various clients. Built with Python, it emphasizes secure handling and compatibility with Claude Desktop via the Smithery ecosystem.

  31 8 MCP
• 40
  

  mcp-log-proxy

  Web-based proxy for inspecting Model Context Protocol traffic in real time.

  mcp-log-proxy enables users to observe and debug messages exchanged between MCP clients and servers through a user-friendly web interface. It supports the STDIO interface and can operate multiple proxy instances, each accessible via a web dashboard. The tool allows customization of ports, web page titles, and log file locations, making it suitable for managing and troubleshooting MCP-based model communication. Installation is straightforward via Homebrew or Go, and it supports real-time switching between different running proxies.

  26 3 MCP
• 41
  

  MCP Ping-Pong Server by Remote Call

  An experimental MCP-based Ping-Pong server leveraging FastAPI and FastMCP for remote calls.

  MCP Ping-Pong Server by Remote Call demonstrates the use of the Model Context Protocol (MCP) for handling command-based interactions via FastAPI. The project provides a backend powered by FastAPI and FastMCP, enabling remote MCP calls through API endpoints and Server-Sent Events (SSE). It includes thread-safe session management, command handling integration, and an interactive UI for engaging with ping, pong, and count operations. Designed as an educational tool, it showcases practical MCP usage for API-driven workflows.

  1 2 MCP
• 42
  

  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
• 43
  

  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.

  497 103 MCP
• 44
  

  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.

  5 1 MCP
• 45
  

  Mattermost MCP Host

  Connects Mattermost to MCP servers, enabling AI agent-powered tool orchestration within chat.

  Mattermost MCP Host integrates the Model Context Protocol (MCP) with Mattermost, utilizing a LangGraph-based AI agent to facilitate seamless user interaction and dynamic tool execution directly in chat. It supports integration with multiple MCP servers, automatically discovers available tools, and allows users to issue commands or natural language requests. Conversational context is maintained in threads, and users can interact directly with MCP servers to manage resources and capabilities.

  27 16 MCP
• 46
  

  MCP Router

  A Unified MCP Server Management App

  MCP Router is a cross-platform desktop application designed to simplify the management of Model Context Protocol (MCP) servers. It enables users to centrally manage, organize, and monitor multiple MCP servers, both locally and remotely, with support for various connection methods. The app offers advanced context organization through Projects and Workspaces, as well as tools toggling and comprehensive logging. With a focus on privacy, all data is stored locally, and integration capabilities allow seamless connection with popular AI tools.

  1,078 95 MCP
• 47
  

  Kubectl MCP Server

  Natural language Kubernetes management for AI assistants using the Model Context Protocol.

  Kubectl MCP Server enables AI assistants such as Claude and Cursor to interact with Kubernetes clusters using natural language through the Model Context Protocol (MCP). It supports a wide range of Kubernetes operations including resource management, Helm integration, monitoring, diagnostics, and advanced security features. The server is designed to handle context-aware commands, maintain session memory, and provide intelligent command construction and explanations. Integration with multiple AI assistants and flexible transport protocols are supported for a seamless user experience.

  734 137 MCP
• 48
  

  Cross-LLM MCP Server

  Unified MCP server for accessing and combining multiple LLM APIs.

  Cross-LLM MCP Server is a Model Context Protocol (MCP) server enabling seamless access to a range of Large Language Model APIs including ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, and Mistral. It provides a unified interface for invoking different LLMs from any MCP-compatible client, allowing users to call and aggregate responses across providers. The server implements eight specialized tools for interacting with these LLMs, each offering configurable options like model selection, temperature, and token limits. Output includes model context details as well as token usage statistics for each response.

  9 5 MCP
• 49
  

  MCP Rubber Duck

  A bridge server for querying multiple OpenAI-compatible LLMs through the Model Context Protocol.

  MCP Rubber Duck acts as an MCP (Model Context Protocol) server that enables users to query and manage multiple OpenAI-compatible large language models from a unified API. It supports parallel querying of various providers, context management across sessions, failover between providers, and response caching. This tool is designed for debugging and experimentation by allowing users to receive diverse AI-driven perspectives from different model endpoints.

  56 7 MCP
• 50
  

  LLM Context

  Reduce friction when providing context to LLMs with smart file selection and rule-based filtering.

  LLM Context streamlines the process of sharing relevant project files and context with large language models. It employs smart file selection and customizable rule-based filtering to ensure only the most pertinent information is provided. The tool supports Model Context Protocol (MCP), allowing AI models to access additional files seamlessly through standardized commands. Integration with MCP enables instant project context sharing during AI conversations, enhancing productivity and collaboration.

  283 26 MCP