"Reading terminal outputs from a Next.js dev server while developing in Cursor" matching MCP servers:

An MCP server that enables AI coding assistants to interact with a local Airflow cluster via its REST API for triggering DAG runs, monitoring status, reading logs, and diagnosing errors.

基于Model Context Protocol (MCP) 的A股实时行情查询服务器，支持查询A股实时价格、历史K线数据、财务信息及市场概况。

MCP server for configuring the konsol Frappe app via the CLI. Enables AI clients to manage dimensions, measures, fact tables, connectors, and schemas using natural language.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables AI assistants to read, create, and modify SAP BW/4HANA modeling objects via the internal REST API, including aDSOs, InfoObjects, transformations, DTPs, queries, and more.

Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.

Enables managing a Yandex Business branch network through an XML feed from any MCP client. Agents can edit branch data in YAML, import/export, validate, diff, and build the feed locally, while publishing to Yandex remains manual.

Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

Provides access to comprehensive financial market data from Massive.com API, including real-time and historical data for stocks, options, forex, crypto, trades, quotes, market snapshots, ticker details, dividends, splits, fundamentals, and market status through an LLM-friendly interface.

Converts PDF, Word, PowerPoint, Excel, and HTML documents into Markdown, handling files up to 8 MB in a single call and routing larger or scanned files through an OCR and table-detection queue that returns Markdown plus a JSON structure file. Results arrive either by polling or a signed webhook.

Connects MCP clients such as Claude Desktop and Claude Code to Opteryx so users can ask questions about their data in plain English, discovering datasets, reading schemas, running queries, profiling columns, and validating SQL. Every call runs as the token's own user and against only the data that user can see.

Connects an AI agent over Streamable HTTP to a workspace so it can read datasets, contracts, runs and receipts, and, when the owner permits, create fields and value sets, start runs and publish releases — while each deployed tool is also served as its own endpoint whose schema is generated from the owner's contracts. Every value comes with a receipt and safety exclusions are enforced in the query, with sensitive actions like approving review items or publishing past the accuracy gate reserved for a person.

Live normalized remote-job data across 5 boards — one keyless endpoint, one schema, skill fit-score. No API key required. Tools: search jobs by skills + salary floor, live market stats, and computed salary bands.

Connect AI assistants to your Metabase analytics platform. Access dashboards, execute queries, and retrieve data seamlessly through conversational interfaces. Enhance your analytics experience with structured data access and robust error handling.

MCP server for DataHub that detects duplicate datasets across platforms and governance gaps, enabling users to apply governance from one twin to another with dry-run by default.

Bidirectional CSV ↔️ JSON ↔️ Markdown transformer exposed as an HTTP-based MCP server, enabling format conversion through natural language.

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

Generate realistic multi-table synthetic datasets from plain English. Supports 18 industry domains, narrative growth curves (Black Friday, Q4 spike, 10x MRR), and 15 locale packs. Works with Claude Desktop, Cursor, Windsurf, Zed, and Continue.

Enables agents to resolve data incidents by preparing remediation, inspecting verification results, and staging for human approval, while integrating with DataHub for evidence.

Enables agents to validate climate-processing configurations, inspect sample CSV data, and run a deterministic pipeline that aggregates daily records into monthly summaries and plots, with sandboxed paths and isolated outputs.