"Building OpenAI Agents SDK Using Official Documentation" matching MCP servers:

Data observability for AI agents. Query alerts, monitor freshness, investigate schema drift, and trace lineage across your data warehouse via 53 MCP tools.

Official MCP server for the s2.dev serverless stream platform

Provides tools for named entity extraction, Wikidata disambiguation, sameAs schema linking, and knowledge graph triple construction, enabling structured semantic data processing.

Official Talonic MCP server. Lets AI agents extract structured, schema-validated data from any document, including PDFs, scans, images, spreadsheets, and forms, directly inside the chat.

A Model Context Protocol (MCP) server that integrates the FAIM time series forecasting SDK with any MCP-compatible AI assistant, enabling AI-powered forecasting capabilities.

Enables preparing data, building and running Mplus input files, and reading the output back as tables, including fit indices, parameter estimates, and warnings.

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

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

MCP server for BIM-to-building-energy simulation workflows with IFC extraction, TEASER integration, scenario modeling, weather binding, and results export for downstream WAT/ROI analysis.

Enables AI agents and assistants to work with a Databricks workspace — SQL, clusters and warehouses, notebooks, Jobs, Lakeflow pipelines, Unity Catalog, Volumes, dashboards, Genie, model serving, Vector Search, Lakebase and Apps — under a safety-first model with read/write/destructive/security classification, confirmation steps for dangerous changes, production resource protection, and a fully read-only mode. Every call is checked against the official Databricks SDK, returns typed schemas and redacted secrets, and unsupported features report an explicit error rather than faking results.

MCP server for building and maintaining Hex notebooks from Claude Code. Wraps the Hex API with design-system-aware chart injection, notebook diagnostics, and full cell lifecycle management.

Enables AI agents to load, query, and analyze IFC building model files, including spatial structures, elements, properties, materials, and geometry.

Enables AI agents to manage Databricks Lakeflow jobs by building and uploading Python wheels and triggering runs with specific arguments. It provides a structured way to orchestrate complex data experiments and monitor execution directly on Databricks clusters.

Provides AI assistants with access to Vega-Lite documentation, visualization examples, and specification validation tools. Enables searching docs, retrieving examples by category, validating JSON specs, and accessing schema information for creating data visualizations.

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 interaction with Fantasy Premier League data through natural language queries. Supports retrieving fixtures, league standings, player performance, and other FPL statistics via the official FPL API.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

A resilient MCP server wrapping FiinQuant/FiinQuantX Python SDK for Claude Desktop and Cursor, providing market data, fundamental analysis, screening, and technical indicators via stdio with timeouts, error envelopes, and free-tier guards.

A Model Context Protocol server that enables working with Building Information Modeling (BIM) files by converting IFC files to fragment format and querying BIM data by category.

A Model Context Protocol (MCP) server that provides a comprehensive interface to the Labellerr SDK for managing annotation projects, datasets, and monitoring operations through AI assistants like Claude Desktop and Cursor.