"A tool or platform for assisting in AI development" matching MCP servers:

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.

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.

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

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 MCP-compatible clients to manage AI agent teams, including agents, Kanban issues, projects, goals, approvals, budgets, and raw API access.

A plugin-oriented Jira capability kernel for AI models, providing 24+ tools for Jira operations including issue search, comments, transitions, and project analysis via a dispatcher and HTTP service.

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 deterministic MCP server that reimplements ai-git-fish workflows (aicommit, aibranch, aipr) with Leantime integration, enabling Claude Code and Codex to perform git operations and manage tickets without an internal LLM.

Enables teams to measure their actual ticket-writing style from GitLab, Jira, or GitHub and check new or draft tickets against that learned house profile, with optional model-backed drafting.

A shared coordination layer for multiple AI coding assistants, exposing a persistent task queue, per-task message threads, and progress tracking via JSON files on disk.

Enables AI assistants to interact with SMB platform APIs for querying business data, managing tasks, accessing connectors, dashboards, and monitoring security.

Enables multiple AI agents and humans working in the same project to share status, exchange messages, and claim files through a local collaboration board. It supports project-specific enablement, conflict-aware file claims, and shared state via SQLite.

Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

Enables autonomous AI-to-AI collaboration between Claude and Gemini to execute complex development projects with minimal human intervention. It provides a role-based system with task dependencies, automated project planning, and continuous execution loops.

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 coding agents to claim, work, and submit tasks on SerenEdge projects by exposing the platform's agent API as MCP tools.

Enables deterministic GitHub issue and pull request delivery workflows, including issue creation, development, verification, PR publication, review, and merge, with strict configuration and admission controls.