Search Results for "development tools"
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Showing 22 open source projects for "development tools"
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Genkit
An open source framework for building AI-powered apps
Genkit is an open-source framework developed by Firebase for building AI-powered applications using familiar code-centric patterns. It simplifies the development, integration, and testing of AI features, providing observability and evaluation tools, and supports various models and platforms for versatile AI application development. -
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Gradle MCP Server
A Model Context Protocol (MCP) server
The Gradle MCP Server is a Model Context Protocol implementation that enables AI tools to interact programmatically with Gradle projects. It uses the Gradle Tooling API to query project information and execute tasks, facilitating seamless integration with AI-driven development tools. -
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All-in-One Model Context Protocol
All-in-one MCP server with AI search, RAG
The All-in-One Model Context Protocol Server is a comprehensive MCP server implementation integrating services like GitLab, Jira, Confluence, YouTube, and more. It provides AI-powered search capabilities and utility tools to enhance development workflows. -
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OctoMind MCP
An MCP server for octomind tools, resources and prompts
The Octomind MCP Server is designed to integrate Octomind's end-to-end testing tools and resources into local development environments. It enables AI-powered interfaces to create, execute, and manage e2e tests, enhancing the testing workflow. -
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MCP Go
A Go implementation of the Model Context Protocol (MCP)
mcp-go is a Go implementation of the Model Context Protocol (MCP), designed to enable seamless integration between Large Language Model (LLM) applications and external data sources and tools. It abstracts the complexities of the protocol and server management, allowing developers to focus on building robust tools. The library is high-level and user-friendly, facilitating the development of MCP servers in Go. -
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Nerve
The Simple Agent Development Kit
Nerve is a developer-friendly Agent Development Kit (ADK) that utilizes YAML and a CLI to define, run, orchestrate, and evaluate LLM-driven agents. It supports declarative setups, tool integration, workflow pipelines, and both MCP client and server roles. Nerve is a simple yet powerful Agent Development Kit (ADK) to build, run, evaluate, and orchestrate LLM-based agents using just YAML and a CLI. -
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Template MCP Server
Template to quickly set up your own MCP server
...It provides a basic server configuration with options for both standard input/output and HTTP transport using FastMCP. The template includes a structured framework for defining MCP tools, resources, and prompts, along with TypeScript configuration and development scripts. -
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Upsonic
The most reliable AI agent framework that supports MCP
Upsonic is a reliability-focused AI agent framework designed for real-world applications. It enables the development of trusted agent workflows within organizations by incorporating advanced reliability features, such as verification layers and output evaluation systems. The framework supports the Model Context Protocol (MCP), facilitating integration with various tools and enhancing agent capabilities. -
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MCP Framework
A framework for writing MCP (Model Context Protocol) servers
The mcp-framework is a TypeScript framework for building Model Context Protocol (MCP) servers elegantly. It provides an out-of-the-box architecture with automatic directory-based discovery for tools, resources, and prompts. The framework offers powerful MCP abstractions, enabling developers to define components in an elegant manner, and includes a CLI to streamline the server setup process. -
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Codex MCP Server
MCP server wrapper for OpenAI Codex CLI
...The system manages communication between the assistant and the Codex CLI, handling sessions, command execution, and structured responses. It allows development tools to delegate complex programming tasks to Codex while maintaining a unified conversational interface inside the editor. -
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Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI collaboration with persistent contextual memory. ... -
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Laravel Boost
Laravel-focused MCP server for augmenting AI powered local development
Boost is a Laravel-first toolkit that supercharges AI-assisted development by giving assistants structured, Laravel-aware context. At its core it runs as an MCP server that exposes a battery of Laravel-specific tools, so an AI agent can explore your app, inspect code and config, and take targeted actions instead of guessing. It ships opinionated, composable guidelines tuned for popular Laravel packages, which helps keep generated code idiomatic and consistent with framework norms. ... -
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AWS MCP Servers
Helping you get the most out of AWS, wherever you use MCP
AWS MCP Servers are a collection of remotely hosted, fully-managed Model Context Protocol (MCP) servers by AWS, providing AI applications with real-time access to AWS documentation, API references, best practices, and infrastructure-management capabilities via natural-language workflows. An MCP Server is a lightweight program that exposes specific capabilities through the standardized Model Context Protocol. Host applications (such as chatbots, IDEs, and other AI tools) have MCP clients that... -
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ModelContextProtocol.NET
A C# SDK implementation of the Model Context Protocol (MCP)
ModelContextProtocol.NET is a C# SDK that implements the Model Context Protocol (MCP), allowing developers to build MCP servers on the .NET platform. It supports standard input/output communication and provides a framework for tool integration. The SDK is compatible with Native AOT, enhancing performance and deployment flexibility. A calculator demo implementation is included to demonstrate its capabilities. Features under development include WebSocket support, resource management, and a... -
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MCP Server Simulator iOS IDB
Enables LLMs to interact with iOS simulators
The MCP Server Simulator for iOS IDB provides a bridge between Large Language Models (LLMs) and iOS simulators, offering comprehensive control through natural language commands. It enables operations such as launching apps, interacting with the UI, and retrieving device information, enhancing the capabilities of AI-driven development tools. -
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MCP Proxy
A TypeScript SSE proxy for MCP servers that use stdio transport
...This enables existing desktop-style MCP servers to be reused by web services and IDEs that prefer HTTP, without modifying the server. The tool can multiplex multiple named STDIO servers behind one proxy instance, simplifying fleet deployments or local development with many tools. It ships prebuilt artifacts and a Homebrew formula for quick install on macOS and Linux, with container images published for broader environments. Releases show steady improvements focused on developer experience and operational flexibility. Overall, it lowers the friction of composing diverse MCP tools into a single reachable endpoint. -
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kMCP
Kubernetes Controller for building, testing and deploying MCP servers
KMCP is a companion toolchain for building, testing, and deploying MCP servers with a workflow that spans local development through Kubernetes production deployments. It includes a CLI for day-to-day development tasks like scaffolding new MCP projects, managing tools, building container images, and running an MCP server locally for validation. For cluster operations, it includes a Kubernetes controller that manages MCP server lifecycles using a dedicated Custom Resource Definition (CRD), allowing MCP servers to be represented as native Kubernetes objects you can operate with familiar kubectl-driven patterns. ... -
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MCP Shrimp Task Manager
Shrimp Task Manager is a task tool built for AI Agents
Shrimp Task Manager is an MCP server that converts natural-language requests into structured development tasks with dependencies, status, and style/format rules—built for agents that reason step-by-step. It emphasizes chain-of-thought and reflection loops, allowing an assistant to plan, refine, and re-prioritize work like a human project assistant. The server exposes typed tools so clients can create tasks, link prerequisites, record progress, and enforce writing or coding standards for consistent output. ... -
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MCPHost
A CLI host application that enables Large Language Models (LLMs)
mcphost is a command-line host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP). It provides a unified interface for engaging with various AI models and supports integration with multiple MCP servers, streamlining the development of AI-driven applications. -
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Browser MCP
Browser MCP is a Model Context Provider (MCP) server
...The repository shows active development and a growing star count, reflecting rapid adoption across agent tooling. -
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FlowLens MCP
Open-source MCP server that gives your coding agent
FlowLens MCP Server is an open-source tool designed to give AI-powered coding agents (like Claude Code, Cursor, GitHub Copilot / Codex, and others) full, replayable browser context to dramatically improve debugging, bug reporting, and regression testing for web applications. It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console... -
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LitterBox
A secure sandbox environment for malware developers and red teamers
...The README frames typical use cases: testing evasion, validating detections, analyzing behavior, and keeping sensitive tooling in-house. Repo metadata and author pages highlight an active security-tools ecosystem around the maintainer, with CI and pull-request activity suggesting ongoing development. The project positions itself as a safe proving ground to reduce surprises in the field while minimizing operational risk. For teams exploring MCP integrations, notes mention pairing with LLM agents for assisted analysis.
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