Search Results for "context" - Page 11
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Showing 1844 open source projects for "context"
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Unredact
A simple tool for reading in poorly redacted documents
...Unlike traditional optical character recognition (OCR), which only reads visible text, Unredact focuses on inferring missing content where redaction has been applied by analyzing surrounding context, font characteristics, and linguistic patterns to produce candidate reconstructions. It accepts a variety of input formats, automatically identifies redacted regions, and then generates text suggestions that are presented alongside visual overlays so users can choose or refine outputs. -
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Crush
The glamourous AI CLI coding agent for your favourite terminal 💘
...With flexible model switching, Crush allows you to change providers mid-session while retaining conversation history. It enhances productivity by combining LSP (Language Server Protocol) support with extensible MCP (Model Context Protocol) integrations for richer coding context and external tool connectivity. Built for portability, it offers first-class support across macOS, Linux, Windows (PowerShell and WSL), and BSD systems. Backed by the Charm ecosystem, Crush is a stable, actively maintained evolution of the original OpenCode project. -
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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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MCP Notion Server
MCP Server for the Notion API, enabling Claude to interact with Notion
The MCP Notion Server is an MCP server implementation that integrates with Notion, allowing AI assistants to interact with and manage Notion content. It facilitates seamless access to Notion's databases and pages. -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Jira MCP
A Go-based MCP (Model Control Protocol) connector for Jira
The Jira MCP is a Go-based MCP connector that enables AI assistants to interact with Atlassian Jira. It provides a seamless interface for performing common Jira operations, including issue management, sprint planning, and workflow transitions. -
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MCP Server (Rad Security)
Rad Security MCP Server
The RAD Security MCP Server is an MCP server that provides AI-powered security insights for Kubernetes and cloud environments. It integrates with the RAD Security platform to enhance security analysis and monitoring. -
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MCP Timeplus
Execute SQL queries and manage databases seamlessly with Timeplus
An MCP server designed for integration with Timeplus, enabling real-time data streaming and analytics through natural language interactions. -
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InfluxDB MCP Server
An MCP Server for querying InfluxDB
An MCP server that provides access to InfluxDB instances using the InfluxDB OSS API v2, enabling operations such as data writing, query execution, and database object management. -
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MCP K8s Eye
MCP Server for kubernetes management and analyze workload status
A tool designed to manage Kubernetes clusters and analyze workload statuses, providing insights and operational capabilities to enhance cluster performance and reliability. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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KOM
Kubernetes Operations Manager
A Kubernetes Operations Manager (kom) that serves as an SDK-level tool, encapsulating functionalities of kubectl and client-go, providing a comprehensive suite of features for managing Kubernetes resources efficiently. -
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K8M
Mini Kubernetes AI Dashboard
An AI-driven Mini Kubernetes Dashboard designed to simplify cluster management, offering a lightweight console tool with integrated large language model capabilities for enhanced operational efficiency. -
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Azure CLI MCP
Talk with Azure using MCP
An MCP server that enables AI assistants to interact with Microsoft Azure via the Azure CLI, allowing tasks such as listing resources, checking configurations, fixing issues, and creating new resources through conversational commands. -
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Macro
Macro is a unified interface for email, messages, tasks, calls, agents
...It is especially useful for teams that want their communication, operations, engineering work, and AI agents to share the same context layer. -
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MiMo Code
Where Models and Agents Co-Evolve
...The tool includes multiple agent modes, including a build mode for development, a plan mode for read-only analysis, and a compose mode for structured workflows. Its persistent memory system stores project notes, checkpoints, scratch notes, and task progress so the assistant can resume work with context. It also supports subagents, goal checking, voice input, MCP connections, and custom provider configuration. MiMo-Code is useful for developers who want an autonomous coding assistant that combines terminal workflows, long-running task management, and project-aware memory. -
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Dify
One API for plugins and datasets, one interface for prompt engineering
...Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement. Out-of-the-box web sites supporting form mode and chat conversation mode A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort Visual data analysis, log review, and annotation for applications -
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Agent-Native
A framework for building agentic apps
...Each capability is defined once as an action that can be called by both the agent and the user interface. The same actions can also be exposed through HTTP, MCP, A2A, and command-line interfaces. Shared data and application state let agents see relevant UI context and immediately surface their work back to users. The framework includes chat, authentication, permissions, skills, memory, automations, agent teams, and PostgreSQL-backed persistence. It supports PGlite for local development and lets developers bring their own models, databases, tools, and infrastructure. Example agents cover meetings, design, slides, analytics, calendars, mail, media, content, and planning. -
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Unity MCP
AI-powered bridge connecting LLMs and advanced AI agents
Unity-MCP is an open-source integration that connects artificial intelligence assistants with the Unity game development environment through the Model Context Protocol. The project enables AI tools such as coding assistants and autonomous agents to interact directly with Unity projects, allowing them to analyze scenes, modify assets, and generate code within the development environment. By exposing Unity editor functionality through MCP tools, the plugin allows external AI systems to understand the structure of a game project and manipulate it programmatically. ... -
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Clicky
AI teacher that lives as a buddy next to your cursor
Clicky is an experimental AI-powered desktop companion designed to act as an interactive, real-time teaching assistant that lives directly alongside the user’s cursor on macOS. It functions as a menu bar application that can observe the user’s screen, interpret context, and provide guidance through both voice and visual cues, effectively simulating the experience of having a human tutor sitting next to you. The system captures screenshots and combines them with voice input to send contextual queries to AI models, which then respond with both spoken explanations and on-screen visual pointers. One of its defining features is the ability to physically “point” at UI elements across multiple monitors using a cursor overlay, helping users navigate complex software step by step. ... -
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Nanocoder
A beautiful local-first coding agent running in your terminal
...The platform supports multiple AI providers through OpenAI-compatible APIs and can also integrate with local model runtimes such as Ollama or LM Studio. Its architecture emphasizes extensibility through custom commands and integration with Model Context Protocol servers that allow the AI agent to access additional tools. -
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Prime Agent
A self-improving RLM agent for coding workflows
Prime Agent is an open-source coding and research agent designed for complex workflows and long-running autonomous tasks. Its Recursive Language Model architecture treats context as programmable variables and subagents as callable functions inside a persistent Python environment. Files, shell commands, tools, context operations, and agent coordination are handled programmatically through the same runtime. Built-in subagents can work in parallel or continue tasks independently while returning results to a parent agent. ... -
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CoStrict
Strict AI coder for enterprises, quality first
...This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. The system integrates repository-wide analysis using retrieval-augmented generation, allowing it to understand large codebases and provide context-aware suggestions, reviews, and modifications. It also incorporates multi-agent or multi-expert verification strategies, ensuring that generated code is validated from multiple perspectives before being accepted. -
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Sol Advisor
Codex-native architect orchestration with Luna and Terra
...The primary Sol session owns requirements, architecture, specifications, verification, and final acceptance. Its default native workflow delegates implementation to a Terra agent and then requires a fresh Sol review in a separate context. An alternative Luna lane can create user-visible Codex application tasks when the user explicitly authorizes that mode. This separation is intended to reduce context contamination while preserving clear responsibility for quality and architectural decisions. The workflow can monitor implementation, inspect diffs, request corrections, coordinate dependent work, and control final approval. ... -
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Ralph
Autonomous AI agent loop that runs until all PRD items are complete
Ralph is an autonomous AI coding loop that repeatedly runs agentic development tools until every item in a product requirements document is complete. It is designed to work with Amp or Claude Code, launching a fresh AI instance on each iteration to avoid context overload. Instead of relying on one long conversation, Ralph keeps progress through git history, a structured prd.json file, and an append-only progress.txt memory file. Each run selects the highest-priority unfinished user story, implements it, runs quality checks, commits passing work, and updates the PRD status. The workflow encourages teams to split features into small, verifiable stories that fit inside a single context window. ... -
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abtop
Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI
...It gives users a real-time view of active Claude Code, Codex CLI, and OpenCode sessions from local process and file state. The dashboard helps developers track token usage, context window percentage, rate limits, child processes, open ports, and multiple active profiles. It is read-only, so it does not require API keys or authentication and does not control the agents it observes. abtop is especially useful for developers running several agents across projects who need quick visibility into cost, quota pressure, context growth, and orphaned processes. ... -
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ByteRover CLI
The portable memory layer for autonomous coding agents
ByteRover CLI is a portable memory layer for autonomous coding agents. It gives developers a way to store, organize, and reuse project knowledge across coding tools and sessions. The project centers on a context tree that can capture important information about a codebase, decisions, patterns, and instructions. It can run as an interactive command-line experience and connect to an LLM of the user’s choice. ByteRover is useful when agents need persistent context instead of starting from scratch every time they enter a project. Its main value is making agent memory more structured, shareable, and practical across teams, tools, and long-running development workflows.
