Kiro Memory

Context7

Official Remote

Discover Context7 MCP, a powerful tool that injects fresh, version-specific code docs and examples from official sources directly into your AI prompts. Say goodbye to outdated or incorrect API info—Context7 ensures your language model answers come with the latest coding references. By simply adding "use context7" to your prompt, you get precise, reliable library documentation and working code snippets without leaving your editor. Designed for smooth integration with many MCP-compatible clients and IDEs, it enhances AI coding assistants with accurate, real-time context that boosts developer productivity and confidence.

Knowledge Graph Memory

Official

Build and query persistent semantic networks for data management. A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

Provides a knowledge graph-enhanced retrieval system that combines vector search with graph-based relationships for persistent memory and contextual information retrieval

Provides a structured thought process management system for maintaining explicit reasoning steps, policy verification, and tool output analysis through persistent memory storage

Provides a persistent, searchable, automatically updated 'second brain' for development by integrating ChromaDB with automated codebase indexing, chat logging, and sequential thinking tools that maintain context across sessions.

Provides persistent memory capabilities through a SQLite-based knowledge graph that stores entities, observations, and relationships with full-text and semantic search using BGE-M3 embeddings for intelligent context retrieval across conversations.

Maintains persistent project context through a structured Memory Bank system of five markdown files that track goals, status, progress, decisions, and patterns with automatic timestamp tracking and workflow guidance for consistent documentation across development sessions.

Structures reasoning processes through defined thought stages, managing a history of thoughts with metadata for transparent, step-by-step problem solving and decision making.

Readwise

Official

Integrates with Readwise to search and retrieve highlights from a user's library, enabling researchers and knowledge workers to reference saved notes during conversations without switching contexts.

Lara Translate

Official

Bridges to the Lara Translation API for accurate, context-aware text translations between languages with automatic language detection capabilities.

GitHub

Official Remote

Extend your developer tools with the GitHub MCP Server—a powerful Model Context Protocol server enhancing automation and AI interactions with GitHub APIs. It supports diverse functionalities like managing workflows, issues, pull requests, repositories, and security alerts. Customize available toolsets to fit your needs, enable dynamic tool discovery to streamline tool usage, and run the server locally or remotely. With read-only mode and support for GitHub Enterprise, this server integrates deeply into your GitHub ecosystem, empowering data extraction and intelligent operations for developers and AI applications. Licensed under MIT, it fosters flexible and advanced GitHub automation.

Manage and execute tasks efficiently with MCP TaskManager in a queue-based system. This server supports planning by accepting and organizing task lists, and execution by delivering tasks one at a time with feedback on completion. It tracks tasks via unique IDs, ensuring smooth workflow coordination through clear stages: planning, executing, and completing. Designed for integration with MCP clients like Claude Desktop, TaskManager simplifies complex task handling and improves automation by providing structured task queues and real-time updates. Its straightforward action parameters allow easy control over task flow, making it a powerful tool for effective task management.

Streamline Jira Cloud integration with this modular MCP server for AI and automation tools. Easily list scrum boards, track issues, add comments, fetch user info, and search users. Designed for extensibility and easy contribution, it helps automate workflows and connect Jira data to custom agents or bots. The server supports key Jira functionalities like retrieving server details and managing issues, all wrapped in a clean, TypeScript-based structure. Whether enhancing existing tools or building new automation, this project simplifies interacting with Jira Cloud via the Model Context Protocol.

Orchestrates AI coding workflows through role-based agents that transition between specialized responsibilities (orchestrator, architect, developer, reviewer, integration engineer) with comprehensive task management, dependency tracking, and execution state persistence.

Azure DevOps

Official

Supercharge your workflow by bringing Azure DevOps commands directly into VS Code. The Azure DevOps MCP Server lets you manage projects, builds, releases, repos, work items, test plans, and more from your editor with simple prompts. Focused, easy-to-use tools offer clear access to Azure DevOps data, making routine tasks faster while keeping complexity out of your way. Perfect for anyone who wants to streamline DevOps work inside their coding environment.

Access Confluence pages and Jira issues via Atlassian API.

Integrates with GitLab's API to enable repository management, issue tracking, merge request handling, and file operations for automated development workflows.

Provides structured problem-solving tools for step-by-step analysis, branching thoughts, and adaptive reasoning strategies in complex decision-making processes.

Integrates with JIRA through REST API v2 to provide complete issue management including retrieval, JQL searching, creation, updates, status transitions, and commenting for development teams and project managers.

Integrates with OmniFocus on macOS using AppleScript to provide complete task and project management capabilities including CRUD operations, perspective views, batch operations, subtask hierarchies, tag management, and custom filtering for productivity workflows.

Provides persistent intelligence infrastructure for codebase analysis through hybrid Rust-TypeScript architecture that combines Tree-sitter AST parsing with semantic concept extraction, developer pattern recognition, and SQLite-based persistence to build contextual understanding of codebases over time, learning from developer behavior and architectural decisions.

Provides persistent memory storage for assistants to create and retrieve memories with filtering options by app name, category, and result limits through a SQLite database with automatic setup.

Provides persistent memory capabilities through a SQLite-based knowledge graph that stores entities, observations, and relationships with full-text and semantic search using BGE-M3 embeddings for intelligent context retrieval across conversations.

TypeScript-based server for tracking project context across sessions, enabling persistent knowledge sharing through modular, markdown-based memory management with support for multiple development modes.

Maintains persistent project context through a structured Memory Bank system of five markdown files that track goals, status, progress, decisions, and patterns with automatic timestamp tracking and workflow guidance for consistent documentation across development sessions.

Production-ready semantic memory management server that stores, retrieves, and manages contextual knowledge across sessions using PostgreSQL with pgvector for vector similarity search, featuring intelligent caching, multi-user support, memory relationships, automatic clustering, and background job processing for persistent AI memory and knowledge management systems.

Memory-powered agent framework that provides persistent memory capabilities across conversations and sessions using vector databases and embeddings, enabling context retention, reasoning pattern recognition, and shared workspace memory for team collaboration.

Database-backed project memory management system that stores decisions, progress tracking, and system patterns in a queryable knowledge graph with vector embeddings for semantic search and comprehensive import/export functionality.