A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.
Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.
An MCP server that integrates with MySQL databases, enabling secure read and write operations through LLM-driven interfaces with support for transaction handling and performance monitoring.
This TypeScript-based MCP server implements a simple notes system, allowing the creation, listing, and summarization of text notes using MCP concepts with note:// URIs and metadata.
Facilitates integration of PrivateGPT with MCP-compatible applications, enabling chat functionalities and secure management of knowledge sources and user access.
Provide all changes of the specified signal name to the model's context. This is useful for large waveform files with many signals where you cannot fit the entire VCD file into the model's context window.