Browse all content tagged with Developer Tools
The GDB MCP Server exposes GNU Debugger’s capabilities to AI assistants and clients, enabling automated, programmatic remote debugging, breakpoint management, multi-session control, and real-time variable inspection within FlowHunt.
The Inbox Zero MCP Server acts as an integration layer between AI assistants and external data sources, APIs, and services, streamlining development workflows by enabling standardized, context-aware automation and data access.
The LSP MCP Server connects Language Server Protocol (LSP) servers to AI assistants, enabling advanced code analysis, intelligent completion, diagnostics, and editor automation through standardized LSP features in FlowHunt.
Nacos-MCP-Router is a powerful MCP Server that centralizes discovery, installation, and proxying of other MCP servers, bridging protocol gaps and orchestrating service interactions for cloud-native and AI-driven workflows.
The OpenRPC MCP Server bridges AI assistants with JSON-RPC-enabled systems using the OpenRPC specification, enabling programmable, dynamic integration with external APIs and services. It empowers developers and AI agents to discover, invoke, and automate remote procedures for enhanced workflows, debugging, and service orchestration.
The Paddle MCP Server bridges AI assistants and the Paddle API, enabling automation of product catalog management, billing, subscriptions, and financial reporting through secure and intelligent workflows in FlowHunt and supported IDEs.
The Remote MacOs Use MCP Server enables AI agents to securely automate, control, and manage remote macOS systems without extra software. It bridges AI assistants to the native macOS environment for tasks like file management, application automation, and developer workflows.
The Salesforce MCP Server connects FlowHunt and AI assistants to Salesforce, enabling secure, conversational access to Salesforce data, schema, and automation via standard Model Context Protocol tools.
Azure MCP Hub is a central resource for discovering, building, and integrating Model Context Protocol (MCP) servers on Azure. It provides guidance, SDKs, and links to accelerate AI agent development with real API integrations across multiple programming languages.
The Bankless Onchain MCP Server enables structured, programmatic access to blockchain data via the Bankless API, supporting AI assistants and developer tools with real-time contract state, event, and transaction queries across multiple networks.
The Cursor MCP Installer is a streamlined Model Context Protocol (MCP) server for the Cursor IDE. It automates the installation and configuration of other MCP servers via git URLs, simplifying AI assistant integration with external tools, APIs, and data sources.
The Cursor Talk To Figma MCP Server bridges Cursor AI environments and Figma, enabling AI-driven automation, analysis, and modification of design files via standardized Model Context Protocol (MCP) endpoints.
DocsMCP is a Model Context Protocol (MCP) server that empowers Large Language Models (LLMs) with real-time access to both local and remote documentation sources, enhancing developer workflows and AI-powered assistance by enabling instant, context-aware documentation lookup.
The Grafbase MCP Server bridges AI assistants and external data sources or APIs, enabling LLMs to access real-time data, automate workflows, and extend capabilities in developer environments.
The Helm Chart CLI MCP Server bridges AI assistants and the Helm package manager for Kubernetes, enabling natural language automation of Helm workflows such as chart installation, repository management, and command execution. Boost developer productivity and streamline Kubernetes operations by exposing Helm’s capabilities to AI-driven tools.
The interactive-mcp MCP Server enables seamless, human-in-the-loop AI workflows by bridging AI agents with users and external systems. It supports cross-platform development, real-time feedback, and custom integration prototyping for enhanced productivity.
MCP GraphQL is a Model Context Protocol (MCP) server that standardizes access to GraphQL APIs, dynamically exposing each query as a tool for AI assistants and developers. It enables seamless integration, data retrieval, and workflow automation with minimal setup.
The mcpignore-filesystem MCP Server brings secure, granular control to AI agent file access by supporting `.mcpignore` patterns. Safeguard sensitive data, automate file tasks, and enable AI-driven development workflows with robust, customizable filesystem interfaces.
The Microsoft Docs MCP Server provides real-time, authoritative access to Microsoft documentation for AI assistants, IDEs, and development tools. Enhance workflows with up-to-date, trustworthy content from Microsoft Learn, Azure, Microsoft 365, and more.
The National Parks MCP Server bridges AI assistants and developer tools with the U.S. National Park Service API, providing real-time access to park data, alerts, visitor information, and campgrounds. Seamlessly integrate up-to-date national park information into apps and AI workflows.
The Neovim MCP Server bridges AI assistants and Neovim, allowing advanced text editing, file navigation, and codebase management directly from your AI-powered workflows. Seamlessly integrate LLM capabilities into your development with automation, intelligent search, and more.
The nx-mcp MCP Server bridges Nx monorepo build tools with AI assistants and LLM workflows via the Model Context Protocol. Automate workspace management, run Nx commands, and empower intelligent project analysis in your Nx-based codebase.
The Obsidian MCP Server bridges AI assistants and Markdown knowledge bases like Obsidian vaults. It enables tools such as Claude Desktop to search, read, and summarize notes, making your personal or team knowledge easily accessible within development workflows.
The Pandoc MCP Server enables seamless, automated document format conversion using the powerful pandoc tool. Integrate it with FlowHunt or other AI systems to transform content between Markdown, DOCX, HTML, and more—while preserving document structure and formatting.
The Semgrep MCP Server connects FlowHunt’s AI agents to the powerful Semgrep code analysis engine, enabling automated security scanning, AI-augmented code review, and seamless compliance enforcement within your development workflows.
The Skyvern MCP (Model Context Protocol) Server bridges AI assistants and external systems, enabling seamless integration with databases, APIs, and file storage to automate workflows and enhance AI capabilities within FlowHunt.
Tianji MCP Server connects AI assistants to external data sources, APIs, and services, bridging AI models with real-world resources for enhanced automation, dynamic workflows, and real-time context in AI-driven applications.
The Verodat MCP Server bridges AI assistants with Verodat’s powerful data management, allowing seamless data access, automation, and workflow integration directly within development environments.
The Vibe Check MCP Server provides AI workflow sanity checks, acting as a strategic pattern interrupt to prevent cascading errors and tunnel vision. Leveraging LearnLM 1.5 Pro (Gemini API), it helps AI systems pause, reflect, and recalibrate, improving code quality and decision-making in complex development pipelines.
The 21st-dev Magic MCP Server empowers developers to generate modern, customizable UI components instantly through natural language prompts, integrating seamlessly with popular IDEs and enabling real-time previews and brand asset management.
The A2A MCP Server bridges Model Context Protocol (MCP) with the Agent-to-Agent (A2A) protocol, enabling MCP-compatible AI assistants like Claude to interact seamlessly with A2A agents for extended automation and orchestration capabilities.
The Code Sandbox MCP Server provides a secure, containerized environment for executing code, enabling AI assistants and developer tools to run, test, and manage code safely using Docker. Ideal for secure code execution, automated testing, and education.
The CodeLogic MCP Server connects FlowHunt and AI programming assistants to CodeLogic’s detailed software dependency data, enabling advanced code analysis, visualization, and automated workflows for improved software development efficiency.
Context Portal (ConPort) is a memory bank MCP server that empowers AI assistants and developer tools by managing structured project context, enabling Retrieval Augmented Generation (RAG) and context-aware coding assistance within IDEs.
DesktopCommander MCP Server empowers AI assistants like Claude with direct desktop automation, providing secure terminal control, file system search, and diff-based file editing for developers. Unlock next-level productivity by bridging conversational AI with hands-on desktop workflows.
The Edgee MCP Server connects AI assistants and LLM-based agents with the Edgee API, enabling advanced organization, project, component, and user management for developers using the Model Context Protocol (MCP).
Integrate Google Analytics 4 (GA4) data with AI assistants and developer tools using the Model Context Protocol (MCP). The Google Analytics MCP Server enables natural language queries, automated reporting, and seamless analytics workflow integration for tools like Claude, Cursor, Windsurf, and FlowHunt.
The JavaFX MCP Server bridges AI assistants and JavaFX-based applications, enabling LLM-powered workflows to interact with JavaFX UI components, automate app state queries, and streamline testing for Java GUIs.
The Lean LSP MCP server bridges AI assistants and Lean Theorem Prover projects using the Language Server Protocol, enabling agents to access diagnostics, goal states, code completion, theorem search, and more for advanced Lean workflow automation.
The MCP-Server-Creator is a meta-server that enables rapid creation and configuration of new Model Context Protocol (MCP) servers. With dynamic code generation, tool building, and resource management, it streamlines the development of custom AI connectivity and integration servers, empowering technical teams to automate workflows and accelerate deployment.
The Multi-Model Advisor MCP Server empowers FlowHunt to connect AI assistants with multiple local Ollama models, enabling simultaneous querying and synthesis of diverse AI perspectives for richer, more nuanced responses.
The Peacock MCP Server demonstrates how an MCP server can connect AI assistants to external APIs within Visual Studio Code, enabling automated theming, workspace identification, and enhanced developer workflows. Ideal as a learning resource or template for building custom MCP servers.
The PubNub MCP Server bridges AI assistants and development environments with real-time communication and external data sources via PubNub’s reliable messaging network. Enhance your coding workflows with live data, seamless API integration, and cross-platform support for platforms like Cursor, Windsurf, Claude Desktop, and more.
The AgentQL MCP Server integrates advanced web data extraction into AI workflows, enabling seamless structured data retrieval from web pages via customizable prompts. Ideal for developers and AI assistants needing real-time, on-demand access to web-based datasets for research, automation, or coding.
The any-chat-completions-mcp MCP Server connects FlowHunt and other tools to any OpenAI SDK-compatible Chat Completion API. It enables seamless integration of multiple LLM providers—including OpenAI, Perplexity, Groq, xAI, and PyroPrompts—by relaying chat-based queries through a unified, simple interface.
Chat MCP is a cross-platform desktop chat application that leverages the Model Context Protocol (MCP) to interface with various Large Language Models (LLMs). It serves as a unified, minimalistic interface for developers and researchers to test, interact with, and configure multiple LLM backends, making it ideal for prototyping and learning MCP.
The Cognee MCP (Model Context Protocol) Server connects AI assistants with external data sources, APIs, and services—enabling streamlined workflows, automation, and expanded AI capabilities for developers.
The forevervm MCP Server bridges AI assistants with external data sources, APIs, and services, enabling real-time integration, workflow automation, and enriched context for AI-driven development in FlowHunt.
The GibsonAI MCP Server connects AI assistants to your GibsonAI projects and databases, enabling natural language management of schemas, queries, deployments, and more—directly from popular development tools.
The GitHub MCP Server enables seamless AI-powered automation and data extraction from the GitHub ecosystem by bridging AI agents and GitHub APIs. Enhance your development workflows and build advanced tools with direct repository access.
The Goat MCP (Model Context Protocol) Server bridges AI assistants with external APIs, databases, and services, enabling advanced automation, tool execution, and context-aware interactions in FlowHunt workflows. Its modular MCP framework makes integration and prototyping seamless for developers.
The GraphQL Schema MCP Server empowers AI assistants and developers to explore, analyze, and document GraphQL schemas programmatically. With a suite of robust tools, it enables schema discovery, type inspection, field lookups, and pattern-based searches, streamlining API integration and documentation workflows.
Hyprmcp is an experimental MCP server that enables language models to control and query the Hyprland Wayland compositor using natural language and AI. Expose powerful Hyprland commands and window management to your FlowHunt agents.
The Inkeep MCP Server connects AI assistants and developer tools to up-to-date product documentation managed in Inkeep, enabling direct, secure, and efficient retrieval of relevant content for RAG workflows, chatbots, and onboarding solutions.
Connect FlowHunt and AI assistants to LeetCode’s coding problems, user profiles, daily challenges, and contest data via the LeetCode MCP Server. Streamline automated coding practice, analytics, and interview prep with seamless API access.
The mcp-server-commands MCP Server bridges AI assistants with secure system command execution, allowing LLMs to interact with the shell, automate development tasks, and manage files directly from FlowHunt and other AI platforms.
The mcp-stdio-to-streamable-http-adapter MCP Server acts as a compatibility bridge, enabling STDIO-based MCP clients to connect seamlessly to modern Streamable HTTP MCP servers. It simplifies integration, testing, and migration, giving developers instant access to new server features without client-side updates.
The Model Context Protocol (MCP) Server bridges AI assistants with external data sources, APIs, and services, enabling streamlined integration of complex workflows and secure management of development tasks in FlowHunt.
The OpenAPI Schema MCP Server exposes OpenAPI specifications to Large Language Models, enabling API exploration, schema search, code generation, and security review by providing structured access to endpoints, parameters, and components.
Reexpress MCP Server brings statistical verification to LLM workflows. Using the Similarity-Distance-Magnitude (SDM) estimator, it delivers robust confidence estimates for AI outputs, adaptive verification, and secure file access—making it a powerful tool for developers and data scientists needing reliable, auditable LLM responses.
The Simulator iOS IDB MCP Server bridges large language models and iOS simulators, enabling AI-driven automation, UI testing, app management, and workflow integration for accelerated app development inside FlowHunt.
The Apollo MCP Server bridges AI assistants with GraphQL APIs, exposing GraphQL operations as MCP tools. It enhances developer workflows by enabling AI-driven queries, mutations, and automation tasks over standardized protocols.
Deepseek Thinker MCP Server integrates Deepseek model reasoning into MCP-enabled AI clients like Claude Desktop, providing advanced chain-of-thought outputs for enhanced AI workflows. Supports both cloud and local inference, ideal for developer debugging, transparent reasoning, and AI agent enrichment.
DevDb MCP Server bridges AI assistants with database development in Visual Studio Code, exposing database operations through the Model Context Protocol (MCP). It enables developers and AI agents to query, manage, and debug databases seamlessly within their editor, boosting productivity and streamlining workflows.
The Dumpling AI MCP Server for FlowHunt enables AI assistants to connect with a wide range of external data sources, APIs, and developer tools. It empowers automated workflows for web scraping, document conversion, knowledge base management, and more, making it ideal for developers and researchers seeking to extend their AI's capabilities.
The GitHub Enterprise MCP Server connects AI assistants to private GitHub Enterprise repositories, enabling automation of repository management, issue tracking, pull request operations, and organizational data insights for enterprise development workflows.
The iTerm MCP Server enables seamless integration between AI assistants and iTerm2 on macOS, allowing programmatic terminal automation, session management, and command execution directly from FlowHunt or LLM-powered workflows.
The Linear MCP Server integrates the Linear project management platform with AI assistants via the Model Context Protocol, enabling automation, querying, and management of issues, projects, teams, and more for streamlined workflows and improved productivity.
The lingo.dev MCP Server bridges AI assistants with external data sources, APIs, and services, enabling structured resource access, prompt templating, and tool execution for advanced LLM workflows.
The Markitdown MCP Server bridges AI assistants with markdown content, enabling automated documentation, content analysis, and markdown file management for enhanced developer workflows.
Integrate your AI agents with Outline documentation using the Outline MCP Server. Enable document search, content management, collection handling, and comment workflows directly in FlowHunt, enhancing organizational knowledge management and developer productivity.
The Redis Cloud API MCP Server bridges AI assistants and MCP clients with Redis Cloud resources, enabling natural language management of accounts, subscriptions, databases, tasks, and configurations. Automate Redis Cloud operations directly from your development tools for enhanced productivity and streamlined cloud workflows.
The tsuki_mcp_filesystem_server is a streamlined MCP server that enables secure search and listing of local filesystem files, providing AI agents with efficient file discovery and management capabilities by exposing the filesystem via the Model Context Protocol.
Gemini Flash 2.0 is setting new standards in AI with enhanced performance, speed, and multimodal capabilities. Explore its potential in real-world applications.
The Model Context Protocol (MCP) is an open standard interface that enables Large Language Models (LLMs) to securely and consistently access external data sources, tools, and capabilities, acting as a 'USB-C' for AI systems.
