"Information about guardrails" matching MCP servers:

Readonly PostgreSQL MCP server with SQL guardrails for analytical queries and schema introspection.

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.

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.

Gives AI agents governed context about a data warehouse — table meaning, ownership, lineage, freshness, and PII flags — plus read-only, row-limited, PII-protected querying across DuckDB, Snowflake, and Databricks. Guardrails enforced at parsing, connection, and result layers keep agents from writing, running away, or leaking personal data.

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

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.

Provides safe read, insert, and update operations on MySQL databases with guardrails against destructive actions.

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.

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

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.

Lets AI clients ask natural-language questions about a SQL database with production-safe guardrails, schema grounding, and read-only enforcement.

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.

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.

Enables Claude to run read-only SQL queries against the DWH.facturas table in SQL Server, including discovering its columns and asking natural-language questions about invoice data.

Lets AI assistants like Cursor and Claude safely explore your database and answer questions about your data in plain English.

Enables users to answer California drinking water questions about public water systems, SAFER risk/violation status, source-water chemistry, school lead sampling, and latest tap/treated-water results by ZIP code or water system ID, using curated Databricks Gold views over State Water Board open data.

A production-grade MCP server for Oracle database interaction, providing 11 tools for full CRUD, transactions, execution plans, and comprehensive safety guardrails.

MCP server to ask research questions about real-world datasets and get actual database records back, with auto-registration and trial credit.

Enables Claude to answer business questions about stock, orders, customer balances, overdue orders and KPIs from live ERP data using fixed, parameterized read-only queries, with bounded results and every call logged to an audit trail.

Provides read-only Arknights intelligence over MCP, enabling structured queries about stages, enemies, operators, and modules with region tagging and evidence-backed analysis. It uses versioned SQLite snapshots and never fetches upstream data at query time.

Enables MCP clients to search and describe API routes, retrieve people, admissions, academics, and billing records, download exports, and optionally make changes against a school information system, read-only by default.

MCP server for running read-only SQL queries across MySQL and PostgreSQL databases with safety guardrails, credentials stored outside source, and support for multiple databases.