"Bitbucket pull request reviewer information" matching MCP servers:

A comprehensive MCP server that provides complete access to Qlik Sense applications and their detailed information for AI assistants and other MCP clients.

Enables AI assistants to create, edit, and export IFC5/IFCX building information models through natural language, handling spatial structure, elements, geometry, metadata, validation, and export.

Enables geospatial analysis by chaining MCP tools that resolve areas, select datasets, pull statistics, and generate insights, with session state passing data between tools.

Enables transforming grounded AI answers into interactive information views such as comparisons, plans, checklists, timelines, and decision views, while preserving a plain-language fallback.

Enables MCP clients to parse charts and chart data out of PDF documents. The deployed service requires a bearer token on every request and rejects any tool argument that the tool's signature does not declare.

Enables visualizing GeoJSON data on an interactive map directly in Claude Desktop, allowing users to request maps of information found or generated.

Enables AI assistants to pull live quotes, quarterly financials, technical indicators, FII/DII flows, option chains with IV, corporate filings, IPO data and portfolio P&L for all 8,200+ NSE and BSE listed stocks, plus a 326-ratio screener and index heatmaps. Connects either remotely over OAuth or locally via npx/uvx to Claude, ChatGPT, Cursor, VS Code, Codex and Gemini CLI.

Enables AI assistants to connect to StarRocks clusters to run read and write SQL, explore databases and table schemas, pull system metrics, and retrieve cached table/database overviews with sample data. It also generates Plotly charts directly from query results.

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

It enables AI assistants to interact with StarRocks databases by running SQL queries, exploring schemas and data, accessing system information, and generating Plotly charts from query results.

Bridges AI assistants with StarRocks databases so they can execute SQL queries and DDL/DML, explore databases, tables and schemas, inspect system metrics, pull detailed table and database overviews, and render query results as Plotly charts.

Bridges AI assistants to StarRocks clusters so they can execute read and write SQL, browse databases, tables and schemas, pull system metrics, and generate table/database overviews or Plotly charts from query results. Connection and behavior are configured through environment variables or a connection URL, with in-memory caching of overviews.

Generates column charts and statistic infographics as PNG images with SVG source links, letting users request finished charts conversationally and receive inline image results.