#MCP
523 related articles
AI Agent Reverse Engineering Games: REA Lets Ghidra Write C Code Automatically
REA is an open-source MCP server plus agent skill that lets an AI coding agent drive Ghidra, IDA, or Hopper with one npx command. In the demo, it starts from DXBall's incomplete decompilation output, rewrites a C function, and passes 3,205 test cases with a 63-byte full match—but the gap between a single function and a complete game is still enormous.
Context Mode Tested: Is the 98% AI Agent Context Reduction Real or Hype?
Context Mode claims 98% AI Agent context compression. We break down the real numbers, community traction, and user feedback.
Anthropic's Official MCP Python SDK: Standardizing AI Agent Tool Integration
Anthropic's official open-source MCP Python SDK turns local async functions into AI Agent-callable tools via the @mcp.tool decorator, supporting stdio and SSE transports, standardizing AI tool discovery and invocation to lower Agent integration costs.
What Exactly Is the Difference Between MCP and Tool Calling?
Is MCP the same as Tool Calling? This article breaks down their essential difference: Tool Calling lets AI request function execution, while MCP provides a standardized communication protocol. With Spring AI scenarios, it explains when to use MCP and when you don't need it.
Connecting Claude Code to Dawnwood via MCP: Running an AI Studio from Your Chat
Dawnwood uses MCP to let Claude Code, Cursor, and Claude Desktop drive an AI studio directly: generate an API Token, log in from the terminal, register the MCP server—about 90 seconds to onboard, with agents handling episode planning, scripts, rendering, and delivery while approval gates stay in human hands.
Fabric IQ MCP Server: What AI Agents Can Read from Power BI
Fabric IQ MCP Server is now GA: Microsoft-hosted, Entra ID delegated sign-in, six read-only tools—letting AI agents query Power BI semantic models directly. We break down its architecture, permission boundaries, when to use it, and how it differs from Fabric Core MCP Server.
Building 6 B2B APIs in 6 Days: A Cloudflare Workers + MCP + x402 Post-Mortem
A developer built 6 B2B API products, 2 MCP servers, and 914 SEO pages in 6 days using Cloudflare Workers + MCP + x402. HS classifier benchmarks 24.5% accuracy at $0.01/call — full stack and growth post-mortem.
Keyword Research Inside AI Chats: A Practical MCP Guide
MCP lets you do keyword research right inside AI chats — no tool switching. A 15-minute workflow covering seed extraction, intent clustering, and AI citation layer checks, with real data from a small team and common failure modes.
MCP Servers: The New Visibility Entry Point in the Age of AI Answer Engines
MCP protocol is changing the visibility rules of AI answer engines. This article explains how MCP servers let tools be called by agents, how to design citable tool descriptions, the real support status of ChatGPT and Perplexity, and how to measure AI citation share.
When AI Queries Your Database, Where Does Your Data Actually Go?
When AI assistants query databases, data travels through four layers: the chat app, the AI model, the MCP server, and the database. Credentials stay in one place, but results travel everywhere. This article traces a query's full journey, maps four places data may linger, and offers five practical ways to shrink your data footprint.
Will MCP Replace API? The Essential Difference Explained in 40 Seconds
Will MCP replace API? No. This article uses a concise comparison to clarify the essential difference: API is designed for programmers, MCP for AI applications — it still calls APIs underneath, an abstraction layer rather than a replacement.
Azure AI Language + MCP: Giving AI Agents Real NLP Capabilities in Practice
Learn how to connect Azure AI Language NLP capabilities to Microsoft Foundry Agent via MCP for language detection, entity extraction, PII detection, plus regional pitfalls and permissions setup.
MCP Protocol Explained: Build Your AI Server with 10 Lines of Python
What is MCP (Model Context Protocol)? This article visualizes the MCP architecture, explains Host/Client/Server roles, the three primitives Tools/Resources/Prompts, and JSON-RPC messaging, demonstrates building an MCP server with 10 lines of Python, and analyzes security risks like tool poisoning.
Using MCP Tools to Let an AI Agent Plan a Portland Walking Route
By connecting Claude Code to GeoAppify MCP, a single prompt lets an AI agent generate a real Portland walking route. Seven tool calls, about 13 credits, showing how the MCP protocol lets an AI travel planning agent connect real places and walking times.
Building a Personal AI Assistant with Hermes Agent: A Practical Guide to Connecting Cloud Servers via MCP
Based on an Indonesian developer's hands-on tutorial, this guide explains how to build a personal AI assistant with Hermes Agent and MCP to remotely manage cloud servers via Telegram.
Five API Failure Lessons from Serving 300 AI Agent Clients
Agent Commons' practical lessons from serving 300 AI Agent clients: Bot protection silent blocking, GET-only limitations, redirects breaking requests, sandbox environments without public IPs, template placeholder submissions—five major API design pitfalls and solutions.
Obsidian 2026: MCP Connects AI Agents with Your Local Knowledge Base
In 2026, Obsidian's knowledge management focus shifts to AI integration: connecting vaults to AI agents via MCP, building local LLM assistants with Smart Connections and Copilot, and balancing privacy with functionality.
MCP vs API: When AI Agents Post to Social Media, Which One Replaces the Other?
Will MCP replace social media APIs? This article breaks down the full chain of AI agent posting: APIs handle deterministic machine-to-machine calls, while MCP wraps platform capabilities into tools for models to discover. They're not replacements — MCP is an adapter built on top of APIs.
Connecting Roblox Studio to Gemini via MCP: A Practical Guide
A complete guide to connecting Roblox Studio to Gemini via MCP: enable MCP Server, use Quick Connect with Gemini CLI, and troubleshoot failures so AI can operate your game project directly.
Multi-Agent + MCP: A Practical AI Solution for Hotel Group Booking
AI/MCP Agent™ platform showcases a multi-agent hotel group booking solution: an operations agent queries PMS for rooms and pricing via MCP, a contracts agent drafts proposals with zero tools and pure reasoning, and structured handoffs keep quotes and contracts consistent—delivered via website, agent assist, and phone.