An MCP server that provides flight search capabilities using the Aviasales API, allowing users to search, filter, and get details on flights and generate booking links.
Connects AI agents to Google Flights data, enabling retrieval of flight information, cheapest options, time-filtered flights, and best recommendations.
Integrates Google Flights data into AI workflows for natural language flight searches, price comparisons, flexible date searches, and multi-city itinerary planning with support for various cabin classes and passenger types.
Enables flight search and price comparison by scraping flight information from Bing Flights. Supports one-way and round-trip searches with customizable passenger counts, cabin classes, and booking details.
Enables searching and retrieving detailed flight information using the Duffel API, supporting various flight types and flexible search parameters for efficient travel planning.
This MCP server allows an AI assistants to search for flight information online using Google Flights. It can find flights for specific dates or search through a range of dates to find all options or just the cheapest ones available.
A remote MCP server that searches Google Flights for flight information and airport codes. It enables users to find flights, locate airports, and generate travel dates through natural language interactions.
Enables searching and retrieving flight information using Duffel API, supporting one-way, round-trip, and multi-city queries with flexible search parameters.
Provides comprehensive A-share (Chinese stock market) data including stock information, historical prices, financial reports, macroeconomic indicators, technical analysis, and valuation metrics through the free Baostock data source.
A memory MCP server with a dual-storage system using ChromaDB and NetworkX DiGraph, enabling efficient data management and integration with IDEs like Cursor and VSCode for enhanced research and note organization.
A Model Context Protocol server focused on China's A-share stock market that provides data on stocks, financials, market indices, and macroeconomic indicators.
A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.
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.
Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.
Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.