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

Enables AI agents to query Korean public data from OpenDART, data.go.kr and law.go.kr — corporate filings and financials, stock prices, apartment trades, business registration status, holidays, statutes in force on a given date, and court rulings. It corrects the live APIs' known traps (mislabeled periods, not-yet-in-force laws, cancelled trades, changed district codes) so answers come back right, with evidence.

MCP server that will proxy to your gRPC backends via reflection or descriptors file.

Enables users to manage their Zaim household account data through OAuth 1.0a authentication. It provides 14 tools to retrieve, create, update, and delete financial records and master data like categories and accounts.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Long-term persistent memory for AI agents with hybrid search (DiskANN + FTS), bi-temporal knowledge graph, and 81.1% LongMemEval accuracy.

Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.

Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.

A Model Context Protocol server enabling AI assistants to query and explore data warehouses via Trino, with optional semantic context from metadata catalogs.

Enables AI agents to capture, store, and retrieve durable learnings from projects via MCP tools, providing a queryable memory of product and technical lessons across repos.

Enables analyzing sales and stock CSV files to identify what to reorder, how much to buy, when products will run out, and how much inventory is tied up in dead stock. Provides read-only inventory checks and CSV column inspection without uploading data.

Enables reading books from Project Gutenberg via MCP, with tools to search books, fetch metadata and full text, and retrieve passages by fixed-size keys.

Records how any command-line tool behaves (flags, stdin, outputs, exit codes, edge cases) as golden tests, then diffs a Rust or Go rewrite against the original to prove it behaves the same.

ZCP is a CLI with Zerops MCP that makes your agent a Zerops power-user. It runs either inside your project, or is connected through zCLI's VPN functionality to the project from your terminal. Your agent. Your subscription. Your code. Your infrastructure. Your IDE.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

Enables AI agents to search and retrieve Italian tax reliability scores (ISA) statistics from Agenzia delle Entrate, including national and regional data, through MCP tools for queries by keyword, year, and code.

Enables AI agents to inspect database schemas and run single read-only statements across PostgreSQL, MySQL, MariaDB, SQLite and MongoDB connections, returning compact TSV results that keep token usage low. Both MCP tools work uniformly regardless of how many connections are configured, and connection names are exposed in the server instructions.

Enables agents to query a dated, provenance-backed history distilled from any text stream, turning raw records into observations, bi-temporal facets, and narratives over MCP.

Enables LLMs to access banking, investment, and cryptocurrency data through a standardized MCP interface, featuring Plaid integration for account and transaction data and Robinhood for crypto trading with audit trails.

Enables AI agents to search and retrieve academic literature from Web of Science and CNKI, with support for institutional login/SSO. Can be deployed locally on Windows or as a remote Linux server.

ContextLattice is an HTTP-first, MCP-compatible memory/context/task orchestrator that persists writes and returns fused recall from specialized stores with local-first defaults. Primary URL: https://contextlattice.io/ Install: https://contextlattice.io/installation.html Troubleshooting: https://contextlattice.io/troubleshooting.html

An MCP server providing web search, image search, and page scraping tools to LLMs without requiring API keys.

Records your terminal sessions per command (PTY + OSC 133) into local SQLite, so AI agents can search, retrieve, and diff what commands actually printed. Secret redaction is applied by default to everything served over MCP.

Serves the review notes left at lines of a diff in seam, a terminal diff viewer, to an agent with the code around them. The agent answers each note, and the answer shows in seam at that line.

Agentic DevOps control loop and MCP server featuring polyglot Tree-sitter AST blast-radius analysis, OPA Rego policy evaluation, and isolated --network=none Docker test verification[cite: 1]. Exposes tools to inspect impacted dependency closures, validate security guardrails, and run targeted test suites.

Model Context Protocol server for the NetLoc8 IP geolocation API. Gives AI assistants access to country/city lookup, timezone reconciliation, and IP utilities.

PCI DSS v4.0.1 compliance scanner for Go payment services, delivered as an MCP server. Every finding maps to a specific PCI DSS requirement ID. Taint-aware cardholder data flow analysis with PCI SSC FAQ semantics, designed to complement broad SAST tools like Semgrep and CodeQL - not replace them.

Turn any OpenAPI/Swagger/Postman spec into an MCP server — give your LLM live access to any API.

GenieACS-MCP is a Go-based MCP server that bridges any GenieACS (TR-069 ACS) instance, exposing device data, firmware management, and CPE actions (reboot, parameter refresh, firmware download) over JSON-RPC

CNCF release intelligence: typed, quoted facts (security fixes, breaking changes, deprecations) from every graduated/incubating project's release notes, updated daily. check_stack compares running versions locally — versions never leave your process.

Uptime monitoring from your AI agent: create and diagnose checks (40 types: HTTP, TCP, DNS, SSL, ICMP, databases, message queues and more), read results and incidents, and manage status pages and maintenance windows. Built into the self-hostable SolidPing server, served over streamable HTTP at /api/v1/mcp.

MCP server that exposes any LynxPrompt instance to LLMs, enabling browsing, searching, and managing AI configuration blueprints and prompt hierarchies.

Your agents, briefed. Not flooded. Self-hosted context compiler: git-backed team knowledge served to coding agents as token-budgeted bundles over MCP.

Enables AI assistants and local LLMs to interact with BirdNET-Go bioacoustic observatories, providing tools to query recent and historical bird detections, monitor station health, and retrieve audio clips.

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

MCP server that exposes any Telegram-Archive instance to LLMs, enabling message search, chat browsing, and access to archived Telegram history.

Baryon connects MCP-compatible AI assistants to Proton Mail through a local bridge, enabling email search, reading, attachment handling, and draft creation while enforcing deliberate permission limits. It runs locally and cannot send, delete, or modify mail.

MCP server that exposes any Pumperly instance to LLMs, enabling real-time fuel price queries, station search, route planning, and geocoding.

Probe LLM API endpoints and report health metrics including time to first token, latency, and throughput.

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.