"Automating a QA End-to-End Workflow" matching MCP servers:

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

A research-informed MCP server that enables natural language question answering over local dataframes (CSV, Parquet, or Pandas) with safe, read-only execution and typed analysis plans.

Enables AI clients to create and read structured research records—projects, questions, specifications, implementations, executions, artifacts, evidence, evaluations, comparisons, analyses, and reports—through MCP while keeping scientific judgments and approvals human-controlled.

提供A股实时行情、历史K线、财务报表、技术指标等全方位数据查询的MCP服务器，支持盘中即时更新及批量查询。

This read-only remote MCP server lets AI clients query a curated catalog for AI-assisted development and agent workflow articles, retrieve recent posts or daily snapshots, and obtain source metadata and links to the originals for review and summarization.

An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.

Provides 11 composable MCP tools for A-share market research, covering quotes, news, technical signals, sector performance, portfolio risk, backtesting, and paper trading, with traceable data sources and calculation basis.

MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.

Provides comprehensive A-share (Chinese stock market) data including stock information, historical prices, financial reports, macroeconomic indicators, technical analysis, and valuation metrics through the free Baostock data source.

Enables remote execution of MATLAB experiments via natural language, with tools for code execution, task management, file transfer, and system diagnostics.

MCP server adapter that exposes A-share stock data tools, prompts, and resources via FastMCP, enabling querying of stocks, K-lines, financials, sectors, and market hot spots through natural language.

Connects Zotero and Obsidian for an AI-assisted academic reading workflow, enabling paper fetching, structured note creation, highlight syncing, and review management.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

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。

Enables users to query Chinese A-share stock data, including stock basics, historical prices, financial reports, and macroeconomic indicators.

Eleven local stdio MCP servers exposing a reproducible EPA SWMM stormwater-modelling workflow: model building, simulation with run manifests and continuity checks, calibration, GIS/QGIS, design storms and climate scenarios, uncertainty analysis, plotting, and modelling memory.

Answers why a specific number in a Chinese listed company moved — margins, cash flow, inventory, management commentary, policy impact — by reading filed reports and IR transcripts and returning figures with the document and announcement number attached. It deliberately refuses price, valuation, and recommendation queries, returning a "gone_by_design" error instead.

Exposes Vedic astrology tools for birth chart, dasha, transit calculations, and question context analysis.

A Python MCP server for querying grant applications and previewing or committing scoped reviewer reassignments.

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

Enables interactive access to JAXA's satellite observation data (precipitation, land surface temperature, NDVI, elevation, soil moisture) via Claude, providing tools for point time series, dataset information, and area image generation.

Enables any MCP client to drive a research-to-report workflow end to end: planning a source-target plan with kill criteria, scoring each fetched source with an explainable 0–100 quality breakdown, and assembling a citation-registry report. Report checking mechanically enforces citation coverage, returning orphan claims as an error list rather than a pass.

A Model Context Protocol server for PyLabRobot that exposes liquid handler, plate reader, thermocycler, and heater-shaker as MCP tools. It ships in simulation mode by default, allowing end-to-end testing without hardware.

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

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Provides 102 tools for end-to-end data science pipelines, enabling data loading, cleaning, visualization, modeling, and reporting via natural language.

Enables AI assistants to drive Kratos Multiphysics finite element simulations end to end, including introspection, scaffolding, execution, and post-processing.

Minds MCP enables AI assistants to run synthetic market research end to end using grounded synthetic customer panels for concept testing, message testing, and segment comparison, with durable server-side studies exporting to PDF, CSV, XLSX, JSON, and Markdown.