"Project dependency resolution and analysis" matching MCP servers:

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

MCP server that transforms Voice of Customer data into actionable customer experience insights through structured analysis and synthesis.

Generate SWOT analyses, competitive comparisons, and browse 100+ pre-built industry examples for any company, brand, or topic. Supports 12 languages.

Enables discovery of a company's public feature board (Canny, Featurebase, Frill, UserVoice, Productboard) from its domain and retrieval of its most-voted requests with votes, status, comments, and the integrations customers ask for. Supports monitoring runs that surface only new requests, status changes, and vote jumps since a prior run using a saved state key.

MCP server for project planning inside Claude. It tracks progress, knows your codebase, and resumes exactly where you left off every session.

Remote MCP server for AI-powered competitor intelligence, enabling real-time analysis of any product URL through tools like analyze_competitor and report retrieval.

MCP server that exposes project status tools (plan, milestones, RAID items, blockers) allowing AI assistants to retrieve and analyze project information via natural language.

Enables agents to fetch app reviews from Apple's App Store and Google Play per country store, newest first, filtered by date or star rating, with each scheduled run returning only reviews not seen before. It also returns a per-app, per-country rating trend row with the current rating, rating count, change since the last run, and the star split of new reviews.

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.

A Model Context Protocol server that provides Monte Carlo forecasting tools for project duration, cost, completion dates, and sensitivity analysis using three-point estimates and historical throughput.

A local MCP server that gives AI agents read access to Roblox experience analytics via the Open Cloud API, exposing 168 metrics and analysis tools for retention, engagement, monetization, and more.

Enables natural language control of OmniPlan 4 on macOS, allowing creation and manipulation of tasks, resources, dependencies, and project metadata through MCP-compatible agents.

Provides market-intelligence tools for researching AI employee opportunities across Egypt, Saudi Arabia, and UAE using Meta ads evidence, with capabilities for competitor analysis, comparison, and evidence retrieval.

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

Mogut — open-source, read-only MCP server for Apple App Store ASO and growth intelligence: keyword research, competitor analysis, review mining, pricing, localization, and reports.

Provides a transparent, deterministic multi-criteria decision analysis engine that ranks options against weighted criteria with exact, explainable results.

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.

Lets an AI agent read a Pyxis dashboard's analytics — overviews, funnels, devices, acquisition, backend requests, visits and project settings — using a read-only access token created by an admin and revocable at any time. It runs locally over stdio, holds no state, and exposes only GET-style reads of the live Pyxis API.

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.

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.