"A platform for analyzing images using automated tools." matching MCP servers:

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.

Provides task and project management tools for AI agents, including todo list management, prioritization frameworks like Eisenhower Matrix and RICE scoring, time estimation using PERT, daily standup generation, and sprint burndown calculation.

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.

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.

A modular multi-server architecture providing development automation, JIRA management, and performance reporting for Claude Code. It features specialized tools for PR health analysis, code reviews, and generating comprehensive team and individual quarterly reports.

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

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.

A production-ready MCP server that connects AI assistants to the D-Tools System Integrator platform, enabling natural language management of AV projects, clients, catalogs, tasks, service orders, and purchase orders.

A Model Context Protocol server providing AI assistants with comprehensive project, task, and subtask management capabilities with project-specific storage.

Provides a read-only MCP interface to Kaiten, letting an agent retrieve cards, spaces, boards, columns, lanes, discussions, checklists, tags, custom properties, sprints and time-tracking reports with paging, filtering and long-text continuation. It also lists card and comment attachments and downloads selected originals as local files, with hashes and safe unique names, for further agent analysis.

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 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 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.

Centralized MCP server for spec-driven AI agent workflows, enabling isolated feature management, task tracking, and implementation with handoff and archiving capabilities across multiple projects and developers.

An MCP server that provides shared memory, kanban board, and agent registry for AI agents to collaborate as a team, with a live dashboard for human oversight.

Enables MCP clients to read a project's Git-backed kickoff, acceptance criteria, handoff package, progress, and next step, and to append validated, audited progress events as project records. It provides short-lived scoped credentials and fail-closed tool allowlisting for safe, resumable AI-assisted development.

Enables voice-driven task management by letting users view, select, complete, and reschedule tasks through natural-language commands and a native confirmation card with date parsing and batch handling.

Enables Codex projects to read Git-backed context, acceptance criteria, progress, and handoff packages, and to append validated, audited progress events with matching project-record commits.