"An analytics platform for tracking and understanding website and app performance" 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.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.

Enables AI coding agents to file and track issues, plan epics with steps, comment as they work, and hand decisions back to the user through a local Markdown- and YAML-backed issue tracker.

Lets an AI assistant read and write business records in plain language, including looking up people, creating and updating tasks, logging time, and pulling utilization reports through a synthetic ops platform or an optional ClickUp adapter.

MCP server wrapping a mock internal ops platform (FastAPI + SQLite) so Claude Code can read and write employee, project, task, and time data through natural language.

Serves a self-contained, browser-side task board into ChatGPT and Claude as an MCP App, letting users organize columns and cards with drag-and-drop, keyboard moves, undo/redo, and JSON export/import while all state stays inside the chat's iframe.

Enables project and task management through a lightweight SQLite database, allowing users to create projects, add categorized tasks, track status changes, and get project statistics through natural language commands.

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.

Enables Claude Code to read and write issues on the Testing Platform via natural language, including listing projects, filtering issues, creating and updating issues, and adding comments.

Enables AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.

A server that enables AI assistants to interact with Linear's project management tools through the Model Context Protocol, supporting features like searching, creating, and updating issues, adding comments, and retrieving user profiles and team information.

Exposes the 个人管家 app's purchasing, expense, todo, project, budget, and analytics data as MCP tools so agents can read and manage records through the app's authenticated business APIs. Each installation logs in with its own account, stores credentials locally, and supports per-install revocation.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

Enables HR to onboard new hires by copying position templates into personalized roadmaps with working-day deadlines, tracking task completion, and automatically finalizing records when all tasks are done.

A standalone MCP server that provides AI tools by proxying requests to the FTC Platform's REST API, enabling tasks like fetching event applications, evaluations, and scoring criteria.

Automates enterprise Power Platform project setup and management via MCP, reducing setup time from weeks to hours through template-based provisioning, Azure DevOps orchestration, and direct API integration.

Enables multi-tenant task management through a remote MCP server with OAuth2 authentication, per-tenant data isolation, rate limiting, and a client SDK.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Enables interacting with Clockify time-tracking data through natural language, providing tools to manage workspaces, projects, time entries, reports, and more via the MCP protocol.

Enables AI assistants to search and manage construction project economic data, including unit price analyses, resource catalogs, budget trees, and price lists, with secure multi-tenant access.

Enables Codex projects to read Git-backed kickoff, acceptance, handoff, progress, and next-step context, and to append validated, audited progress events through scoped MCP tools. This supports visible agent progress, resumable sessions, and safer handoffs.

Enables Codex and other MCP clients to read kickoff cards, acceptance criteria, Git evidence, and next steps, then append validated, audited progress events for resumable project handoffs.

Enables AI-powered project management by connecting Claude to Planka kanban boards via 75+ MCP tools for creating, updating, and managing projects, boards, lists, and cards.

Enables agents to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited progress events with matching Git commits through short-lived scoped credentials.

Enables AI agents to retrieve Git-backed project context, handoff packages, progress, and next steps, and to append validated progress events with matching project-record commits. This supports visible agent progress, resumable work, and safe handoffs while keeping high-risk actions outside the MCP surface.

Enables agents to read Git-backed project context and append audited, idempotent progress events through scoped, short-lived credentials, supporting resumable handoffs and visible project state.

Enables AI agents and users to verify claims about Jira issues and issue counts against live Jira, retrieve verifiable facts for drafting updates, and re-check previously posted claims. It provides read-only tools and an issue panel so status updates can be evidence-based and mismatches corrected before or after posting.

Enables Codex sessions to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail, and next step, then append validated, idempotent progress events backed by matching project-record Git commits. Access is limited to a short-lived, revocable credential scoped to one workspace and project, with high-risk actions kept outside the server.