"Information about SQL (Structured Query Language)" matching MCP servers:

A Python-based MCP server that enables AI agents to query the Microsoft 365 Roadmap programmatically.

Provides a comprehensive creative thinking tool with methods like structured process, perspective shift, and constraint-based innovation to enhance divergent thinking.

Feedback collection for AI agents. Create surveys from JSON schema, collect responses from groups of people, and retrieve structured results.

An MCP server for accelerator programs to query, review, and manage startup applications via natural language. It enables searching applications by sector or impact score, fetching full application details with reviewer notes, listing pending reviews, and flagging applications for panel discussion.

Enables AI assistants to identify and quantify value leaks in organizations using Melt's methodology, providing structured estimates instead of generic vendor lists.

An MCP server for Capacities API 2.0 that enables AI agents to discover, create, read, update, and delete objects, blocks, and daily notes with structured JSON or Markdown, using personal API tokens.

Enables AI assistants to perform structured decision-making using the Analytic Hierarchy Process (AHP), allowing users to define criteria, compare options pairwise, and calculate ranked results with consistency validation.

An AI-native product development pipeline that guides users from idea to shipping with structured research, architecture, build, validation, and traceability using 52 tools across 4 domains.

Enables MCP clients to query the IndeCX public API for survey data, including actions, questionnaires, answers, invites, non-respondents, categories, blocklists, and branches.

A Model Context Protocol server for FeaturePulse feedback management, enabling AI assistants to query feature requests, analyze MRR impact, and manage product roadmaps through natural language.

Enables AI agents to query real-time SaaS pricing tiers, compare developer tools side-by-side, and retrieve recent product changelogs.

Enables users to stress-test decisions and plans with structured contrarian analysis, surfacing blind spots, hidden assumptions, and failure scenarios through multiple modes such as counter, probe, redteam, and premortem.

Prevents premature AI coding by transforming vague product ideas into structured specifications, architecture decisions, and acceptance criteria through a series of interrogation and compilation tools.

MCP server that connects to Jira Data Center, enabling issue search, retrieval, creation, comments, workflow transitions, project listing, arbitrary JQL, and turning meeting notes into structured Jira stories, tasks, and bugs.

MCP server for reading public Featurebase feedback boards, enabling agents to query user feedback, posts, comments, and statistics.

Provides a governed analytics layer over synthetic product data, exposing MCP tools for investigating product metrics, slicing by dimensions, and comparing periods while preventing unrestricted SQL access.

Enables interaction with PostHog analytics platform, allowing users to list projects, create annotations, and search insights through natural language in Claude Desktop.

Model Context Protocol server that enables AI assistants to query and analyze project feedback and bug reports from FeedbackBasket projects, with filtering by category, status, sentiment, and search capabilities.

A Model Context Protocol (MCP) server that connects Trello to Claude Code. Manage your boards, lists, cards, checklists, and more — all through natural language.

Run real user interviews from AI agents and retrieve structured insights with themes and verbatim quotes.