"Technology stack recommendations for software projects" matching MCP servers:

Enables conversion of business briefs or authenticated saved projects into structured handoffs for the Lovable plugin, with both anonymous basic mode and authenticated full mode including knowledge base, SEO, WCAG, security, and roadmap guidance.

MCP server for Taiga project management, enabling LLM clients to inspect and manage projects, work items, sprints, comments, attachments, and wiki pages via 6 op-dispatching tools.

Enables AI assistants such as Claude, Cursor, and Codex to pull structured, source-backed, dated competitive intelligence — positioning, pricing, ads, social, reviews, hiring, momentum, and exploitable weaknesses — for any company in the universe, alongside the user's own projects, reports, battlecards, timelines, and evidence. Read-only by default, with optional opt-in competitor creation and plan-gated tools for deeper analysis.

Enables AI assistants to search and retrieve verified software comparisons, including current pricing with source and date, and ranked alternatives for software switching decisions.

MCP server that enables structured decision-making using weighted decision matrices, sensitivity analysis, and robust recommendations.

A deterministic what-if scenario simulation MCP server that projects business metrics over time with exact decimal arithmetic, offering sensitivity analysis and break-even solving.

MCP server for IDEA Base — AI-powered project management. Manage projects, tasks, and time tracking directly from Claude Code, Cursor, or any MCP-compatible AI tool.

Enables managing software delivery from intake through stabilization via an evidence-gated hierarchical state machine, with tools for transitions, work items, blocking, resuming, and status rendering.

An MCP server that enables AI tools to interact with the Lalaleap project management system using natural language, allowing creation and management of requirements, bugs, todos, and projects.

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

Enables MCP clients to read and manage Linear issues, sub-issues, relations, comments, projects, cycles, teams, users, labels, and workflow states using a personal API key.

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.

Enables AI clients to read and manage Plane projects, work items, states, labels, cycles, modules, members, and comments via the Plane REST API.

MCP server for Ithura, enabling AI assistants to read and write tasks, sprints, projects, modules, wiki pages, and intake via natural language.

Enables agents to analyze cart items and intent, compute product complementary affinity scores, respect merchant margin constraints, and synthesize personalized discount bundles for cross-sell recommendations.

Official MCP server for FeatureJet, enabling agents to read and act on customer feedback boards: list/search posts, file feature requests, and pull top-voted planned items.

MCP server for managing Tokei pre-launch and waitlist campaigns, wrapping the Tokei v1 REST API. Enables querying pages, stats, leaderboards, signups, and performing write operations like cloning pages and uploading media through natural language.

A federated MCP server that combines IBM's engineering-ai-hub tools with its own authoring and orchestration tools for IBM ELM, enabling AI hosts to manage requirements, models, and compliance through a single interface.

Enables Claude Code to run multi-round grilling sessions in a browser UI, publishing rounds of questions with options and recommendations that users answer with buttons or free text. Supports per-question asides (re-pitch, visual diagram, plain-language explainer), chat notes between rounds, and a polling contract so sessions can stay open without blocking the client.

Enables AI assistants to conduct research, plan projects, generate PRDs, user stories and task lists, scaffold full-stack starter kits, map codebases, curate context, and execute multi-step development workflows.