"Information about computer usage" matching MCP servers:

An MCP Server implementation that integrates the Balldontlie API, to provide information about players, teams and games for the NBA, NFL and MLB.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.

Enables AI assistants to securely access and interact with Simplicate business data including CRM, projects, timesheets, and invoices through natural language. Supports searching across resources and retrieving detailed information about organizations, contacts, and project data.

A Model Context Protocol server that provides natural language access to Cortex API, enabling users to query information about their system's structure and make faster decisions about services, incidents, and team responsibilities.

An MCP server that provides detailed information about your development environment to the Cursor code editor, enabling more context-aware assistance.

Enables asking operational questions in Portuguese about a computer repair shop's queue, turnaround times, bottlenecks, technician productivity, sales, stock and individual machines, with answers computed from the real system database. Exposes read-only business tools and ready-made prompts for weekly reports, bottleneck diagnosis and customer-facing order status replies.

A Python-based server that interacts with EPICS process variables, allowing users to retrieve PV values, set PV values, and fetch detailed information about PVs through a standardized interface.

An MCP server that provides standardized access to Pokemon data, allowing users to search, compare, and retrieve detailed information about Pokemon through natural language tools.

Enables AI-powered natural language queries about BIT Information Portal (BIP) data by integrating with BIP APIs through session management. Uses Google Gemini to intelligently route questions to appropriate endpoints and generate contextual answers about students, departments, courses, faculty, and achievements.

Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.

Retrieves comprehensive patient information including personal details, insurance plans, and employee data through the get_patient tool. Supports Docker Compose deployment and integration with Watson Orchestrate for healthcare data access.

A server that allows AI agents to query and retrieve information about upcoming events at Berghain nightclub through a DynamoDB-backed FastAPI service.

Enables searching and retrieving detailed information about Swedish companies, including financial data and annual reports from Bolagsverket (Swedish Companies Registration Office), with intelligent caching for fast responses.

MCP server that allows AI assistants to query and retrieve information about office supplies inventory from a CSV file.

Enables natural language analysis of Azure usage data from CSV files, providing cost summaries, visualizations, and insights about service and regional spending patterns.

A read-only DuckDB MCP server offering context-efficient analytics tools (list_datasets, describe_table, profile_column, explain, query) with a semantic layer for business rules, security guards, and disclosed truncation to help LLMs produce correct answers while minimizing token usage.

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

Enables AI agents to answer analytical questions about an online store's SQLite database through specialized read-only tools, without any risk of modifying the underlying data.