Your MCP server eats 55,000 tokens before your agent says a word -- I measured t

<p>MCP is one of the most thoughtfully scoped technical standards to come out of the AI ecosystem. That scope is intentional. Understanding exactly where MCP stops is the

<p>The AI world has a plumbing problem. We have incredible language models, but connecting them to real tools — databases, APIs, file systems, other agents — still feels like

<p>And you probably have no idea.</p> <p>If you have an agent with 50 MCP tools installed, here's what happens before any user message is processed:<br /> </p> <div

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1wxfdt9/qwen38_27b_1_x_r9700_262k_context_half_a_million/"> <img alt="Qwen3.8 27B | 1 x R9700: 262K context,

<p>In January and February 2026, security researchers filed <a href="https://www.heyuan110.com/posts/ai/2026-03-10-mcp-security-2026/" rel="noopener noreferrer">30 CVEs against

<p>REST APIs gave humans (and the code they wrote) a standardized way to access software over the network.</p> <p>MCP is trying to do the same thing for agents.</p> <p>That simple

<blockquote> <p><em><strong>Originally published on <a href="https://andrew.ooo/posts/agentmemory-persistent-memory-ai-coding-agents-review/" rel="noopener

<p>When I built the MCP server for this project — it combines GitHub and DEV.to into a set of tools an agent can call — I had a decision to make before writing a single tool: talk