Enables to perform mathematical calculations, retrieve weather information, and manage files through a standardized MCP interface, showcasing best practices for building MCP servers.
Enables AI agents to plan software collaboratively with humans by creating and editing graph structures over MCP, then exporting them as Markdown trees and Obsidian Canvas files.
Automatically generates structured agile backlogs including epics, features, and user stories from natural language descriptions within AI-powered IDEs. It streamlines project management by creating AI-optimized markdown files and directory structures to guide step-by-step implementation.
Turns product ideas into implementation-ready planning packages including PRD, requirements, user flow, wireframes, data schema, API contracts, and SDK boundaries, with an MCP handoff for coding agents.
Enables AI agents to decompose high-level goals into structured task plan DAGs with dependencies, acceptance criteria, and quality gates, and to validate or export those plans in multiple formats.
Enables managing daily change logs with automatic formatting, intelligent monitoring, and client-ready output, helping developers document work and generate professional reports.
Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.
A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.
Token-optimized MCP server that integrates Google Gemini CLI for AI-powered coding assistance with 43.8% token savings through progressive disclosure, supporting multi-turn conversations and multiple Gemini models.
Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.
A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.
Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.
Stdio MCP server for managing recommended.by lists from agents like OpenClaw, Codex, Claude Desktop, etc. It exposes tools to create, read, update, delete lists and items via the recommended.by REST API.
A remote MCP server template for Cloudflare Workers that enables deploying custom tools without authentication and connecting to MCP clients like Claude Desktop.