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MCP for project management

The Model Context Protocol (MCP) is becoming the standard way to connect AI tools to real systems — including the system where your team plans and delivers work. Instead of pasting context into prompts, an MCP client like Claude, Cursor, or Claude Code reads your actual projects, documents, and missions, and acts on them under real permissions.

This hub collects everything we publish on MCP: explainers of the protocol itself, integration guides, and analyses of what MCP changes for AI coding tools and project delivery. Every article is dated, reviewed, and updated as the ecosystem moves.

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MCP vs REST API: which architecture should you choose for AI agents?
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MCP vs REST API: which architecture should you choose for AI agents?

MCP or REST API for an AI agent? Choose based on who picks the operation: the code, the model, or both in a hybrid architecture.

10 min read
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MCP for AI Coding Tools in 2026: What Actually Changes
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MCP for AI Coding Tools in 2026: What Actually Changes

A practical guide to MCP for AI coding tools: architecture, client support, security, workflows, limitations, and an evaluation checklist for 2026.

11 min read
How to Connect AI Agents to Stellary via MCP
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How to Connect AI Agents to Stellary via MCP

Connect Cursor, Claude Code, Claude Desktop, or an external agent to Stellary through MCP, with the right endpoint, identity, permissions, and autonomy mode.

6 min read
MCP Explained: How the Model Context Protocol Works
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MCP Explained: How the Model Context Protocol Works

A practical explanation of MCP architecture, tools, resources, transports, permissions, and the compatibility limits teams should understand before connecting AI to work systems.

6 min read
API-First Project Management: Why You Need an API
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API-First Project Management: Why You Need an API

Why API-first PM tools outperform closed ecosystems. How REST APIs, MCP, and programmable workflows enable modern project operations.

4 min read
Why Context Matters for AI Project Assistants
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Why Context Matters for AI Project Assistants

Learn how fresh, scoped, attributable project context improves AI assistants—and why retrieval, memory, permissions, and model training are different systems.

7 min read