"Unreal Engine" matching MCP servers:

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

An MCP server that enables AI assistants to interact with Tenzir, a data pipeline engine for security operations, including executing pipeline queries, managing OCSF schemas, and generating parsers.

Autonomous cross-source inconsistency and contradiction intelligence engine for AI agents. Detects specification drift, SemVer conflicts, and infrastructure mismatches across code, docs, and deployments.

Enables AI agents to work with a real Excel-compatible spreadsheet engine, allowing them to create and manipulate structured data blocks, write and evaluate formulas, and save genuine .xlsx files with live formulas for human verification and reuse.

Enables AI agents to protect, unprotect, and search sensitive data using Kustodyan's contextual transform engine with role-based access controls.

A Model Context Protocol server that enables large language models to access database metadata and perform cross-engine data querying across diverse database ecosystems.

A minimal MCP server that provides a persistent DuckDB SQL engine to AI assistants, enabling natural-language querying of CSVs, Parquet, and cloud data with 12 tools and optional read-only mode.

Enables AI assistants to interact seamlessly with IBM watsonx.data lakehouses using natural language for operations like querying, catalog browsing, engine management, and data ingestion.

Provides secure, agentic Excel analysis and calculation capabilities, enabling users to inspect workbook structure, perform statistical computations, write formulas, and generate outputs through whitelisted MCP tools with audit trails and backups.

Declarative BIM and Building-as-Code engine for AI agents: model buildings in YAML, compute deterministic QTO and cost estimations, compile to IFC4, and view interactive 3D WebGL models.

Enables AI assistants to perform financial reconciliation with a deterministic proof engine: intake files, match transactions, verify proofs, resolve exceptions, and sign off on balanced journals under the user's authority.

A comprehensive MCP server that turns any AI assistant into a powerful mathematical computation engine, providing 52 advanced functions, 158 unit conversions, financial calculations, and secure AST-based evaluation.

Read-only MCP server for FP&A & management reporting — governed metrics, financial statements and drill-down over a SQL semantic layer. Your own financials on your own warehouse, not market data. Open core of Précis. (metric engine · ClickHouse · OIDC · Docker)

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.

Exposes materials-science data, simulations, workflows, and computing capabilities to MCP hosts through a plugin-agnostic, contract-governed engine with progressive capability discovery, bounded context, scoped permissions, and provenance-traceable artifacts. Concrete integrations such as a real OPTIMADE provider plugin stay separately packaged, so servers remain focused and evidence-backed rather than unrestricted.

Enables users to interact with MFlowy, an MCP-native modular ML workflow engine with data analysis, model training, and orchestration.

A local MCP server enabling AI assistants to query and analyze data via DuckDB SQL engine, supporting local files, memory, S3, and MotherDuck.

Enables AI agents and MCP hosts to query Trino while carrying each end user's verified OIDC identity, so row filters, column masks, and catalog scope are enforced by the existing policy engine rather than a shared service account. Queries are read-only by construction, with quotas, revocation, and audit logging.

Connects AI agents to the ODGS Sovereign Validation Engine for deterministic governance enforcement, producing cryptographically signed S-Certs for auditable compliance with regulations like EU AI Act.

Enables local offline machine learning workflows, including CSV profiling and cleaning, classifier and neural network training, hyperparameter optimization, evaluation metrics, confusion matrix plots, Streamlit dashboards, and HTML reports through MCP tools.