"Understanding High-Level Control Systems" matching MCP servers:

Enables MCP clients to discover processor and controller service types, build and wire Apache NiFi 2.x process groups, schedule them, and debug queues and bulletins through the NiFi REST API. Supports flow spec application, automatic canvas layout, parameter contexts, and an optional read-only mode that blocks all writes.

MCP server for PullPush.ai integration sync engine, providing 43 tools to manage connectors, flows, sync operations, diagnostics, and more through the Model Context Protocol.

Bridges Microsoft Clarity's analytics API with Claude, enabling custom date ranges and page-level filtering on top of Clarity's native limitations.

A high-performance Model Context Protocol server for AI integration with Metabase analytics platforms. Features response optimization, robust error handling, and comprehensive data access tools.

Unified MCP server for Arpe.io data tools enabling AI assistants to build, preview, and execute high-performance data commands including database export, transfer, pipeline, and migration.

This MCP server enables database migration between heterogeneous systems (Oracle, PostgreSQL, SQL Server, Netezza to PostgreSQL or SQL Server) through AI assistants by providing tools for command preview, execution, validation, and workflow suggestions.

Enables SQL lineage analysis, including table-level and column-level lineage, field-level tracing, and support for multiple SQL dialects via sqlglot.

Resolves messy company, customer, and vendor names across CRM, ERP, and ITSM systems to canonical records using fuzzy matching, preventing AI agents from updating or creating wrong or duplicate records.

An MCP server that extracts fields from documents and holds uncertain extractions for human review, ensuring high confidence data flows automatically while uncertain cases are resolved manually.

Enables LLM agents to interact with a SQLMesh project, providing model metadata, column-level lineage, plan previews, audits/tests, and environment diffs, with optional apply/run actions.

Vizro is a low-code toolkit for building high-quality data visualization apps.

Enables AI agents to propose and validate data-cleaning recipes, then receive four-way DuckDB comparisons that separate data, recipe, and interaction effects with exact decimal attribution and row-level provenance.

MCP server that unifies real-time telemetry from industrial systems into a single queryable interface, enabling production visibility, anomaly detection, and operational insights.

Production-ready MCP server that enables AI assistants to seamlessly interact with SAP Datasphere environments for real tenant data discovery, metadata exploration, analytics operations, ETL data extraction, database user management, data lineage analysis, and column-level data profiling.

A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.

A high-performance Model Context Protocol (MCP) server that provides seamless integration with Amazon DataZone services. This server enables AI assistants and applications to interact with Amazon DataZone APIs through a standardized interface.

Enables structured document understanding of local PDFs via a dual-extract MCP server, combining MinerU text/layout and Qwen3-VL vision with fusion adjudication for field extraction, tables, formulas, and validation. Fully local and offline.

Enables AI agents to work end-to-end with Power BI and Fabric through 26 high-level tools that orchestrate specialized engines for semantic modeling, report authoring, cloud operations, validation, and visualization UX.

Enables comprehensive interaction with DHIS2 health information systems through 40+ tools covering complete Web API functionality. Supports data management, tracker programs, analytics, and bulk operations for DHIS2 development and administration.

Enables high-precision detection, anonymization, encryption and decryption of personally identifiable information (PII) in text using GPT-4o-based detection and advanced cryptographic methods. Supports both deterministic encryption for searchable data and format-preserving encryption for structured identifiers.