"How to retrieve data from Power BI" matching MCP servers:

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

An intelligent MCP server that analyzes projects and recommends professional role assignments, enabling users to download specialized agent templates for 100+ roles across various company departments.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Enables MCP clients such as Claude Desktop to hand tasks to a running DeepSeek Harness window, where each task becomes a real session visible in the sidebar with a reusable session id. If the in-process plugin is unavailable, it falls back to running the task headless so the tool still returns a result.

Turns any OpenAPI/Swagger specification into a functional MCP server, dynamically exposing API endpoints as LLM tools or generating standalone Python code.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Enables enterprise work agents to decompose high-level business objectives into topological sub-tasks and directly synthesize final deliverables such as financial spreadsheets, executive presentations, and analytical reports.

Bridges Agent Communication Protocol (ACP) agents with Model Context Protocol (MCP) applications, allowing MCP clients such as Claude Desktop to discover and invoke ACP agents as tools and resources.

A middleware API that connects AI assistants like ChatGPT to Captain Data tools for extracting information from LinkedIn company and profile pages.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Google Data Catalog (beta): https://www.cdata.com/download/download.aspx?sku=HGZK-V&type=beta

Shape-shifting MCP hub — shapeshift() into 10,000+ servers at runtime. One entry point, no restarts, 7 registries.

Enables two-model orchestration where Gemini in Google Antigravity delegates coding tasks to Qwen 3.8 Max in Qwen Studio Desktop via CDP, managing prompt delivery, file generation, continuation, and verification.

Enables AI agents to manage Kanban boards, cards, sessions, and automations through a unified MCP interface with real-time updates, supporting delegation, agent sessions, and human-in-the-loop interactions.

A full-stack template for building Model Context Protocol (MCP) servers with a modern React frontend, allowing developers to create AI agent tools and workflows while providing a beautiful web interface.

A proxy server that bridges AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools, enabling seamless interaction without custom integration code.

Acts as a proxy between a local Stdio connection and a remote Model Context Protocol server running over Server-Sent Events. It specifically enables Stdio-based MCP clients to connect to the SwiftZilla remote SSE endpoint.

An open source registry and proxy that federates MCP, A2A, and REST/gRPC APIs with centralized governance, discovery, and observability. It optimizes agent and tool calling, and supports plugins.

A Model Context Protocol server that provides financial tools for retrieving real-time stock data, analyst recommendations, financial statements, and web search capabilities for a LangGraph-powered ReAct agent.

Enables deployment of a customizable MCP server on Cloudflare Workers without authentication. Allows users to define custom tools and connect to clients like Claude Desktop or Cloudflare AI Playground for remote tool execution.

Enables AI agents to perform professional-grade deep research by aggregating real-time data from multiple sources, evaluating source credibility, and generating comprehensive reports.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Enables routing tasks to the right specialist agents, assembling the needed context from a layered catalog of agents, skills, knowledge, runbooks, topics, tools, and connectors, while remembering how a business wants work done.

Teach any AI agent how you use an MCP server – Soft-Landing to your AI integrations

A server that provides AgentQL's data extraction capabilities enabling AI agents to get structured data from unstructured web

A universal interface that enables AI Agents to communicate with Hologres databases, allowing them to retrieve database metadata and execute SQL operations.

A Model Context Protocol server that bridges LLMs (like Claude) with the Fitbit API, allowing the LLM to request and retrieve user health and fitness data through defined tools.

A Model Context Protocol implementation that enables AI agents to retrieve game data from OP.GG for League of Legends, Teamfight Tactics, Valorant, and esports through function calling.

Enables AI assistants to interact with the Apify platform to manage actors, monitor runs, and retrieve scraped data from datasets. It supports natural language commands for executing web scrapers, managing tasks, and accessing key-value stores.

Connect AI agents to OP.GG Esports data and retrieve upcoming League of Legends match schedules effortlessly. Access structured match information through a standardized interface, enhancing your AI's capabilities with real-time esports data.

A shared, living memory hub for AI agents — bi-temporal facts, first-class decisions, and owner-resolved conflicts, served over MCP. Local-first.

An MCP server that provides web search capabilities through the Tavily API and weather data retrieval tools. It demonstrates how to integrate external APIs into AI applications and build agentic workflows with LangGraph.

A Model Context Protocol (MCP) server that demonstrates how to build and implement custom tools for Claude using the mcp-framework.