Enables AI assistants to access the Open Food Facts database to query detailed food product information, nutritional data, and environmental scores. Supports product lookup by barcode, smart search with filtering, nutritional analysis, product comparison, and dietary recommendations to help users make informed food choices.
Provides comprehensive food hierarchy and nutrition data through structured tools that enable searching foods, browsing categories, and retrieving detailed nutritional information from a MongoDB Atlas database.
Enables tracking food intake and nutrition using the USDA FoodData Central database. Supports logging meals, setting daily nutrition goals, viewing food diaries, and analyzing nutrition trends over time with local SQLite storage.
Enables large language models to directly access and search content in ZIM files, allowing offline question answering and information retrieval from resources like Wikipedia.
Provides Kanban, Gantt, list views, multi-project management, and archiving for task management via MCP protocol, enabling Cherry Studio Agent to create, update, query, and organize tasks.
Provides AI assistants with persistent graph-based memory capabilities using Neo4j, enabling semantic search, relationship tracking, and knowledge organization across multiple project contexts.
Universal documentation knowledge-graph MCP server with hybrid full-text + vector search. Indexes local files and remote sources from Notion, Jira, Obsidian, Linear, GitHub, and Confluence into a single SQLite knowledge graph, exposing it to AI agents via the Model Context Protocol.
A demonstration implementation of a Model Context Protocol server that provides simple mathematical tools (add, subtract) and personalized greeting resources.
Enables AI assistants to fully interact with Odoo ERP instances over XML-RPC, supporting read and write operations on any model without requiring Odoo module installation.
