From c4a32d80b3fa8cde7099413f94ff0b728dd77f56 Mon Sep 17 00:00:00 2001 From: Gracjan Date: Fri, 27 Feb 2026 12:35:54 +0000 Subject: [PATCH] feat: update heading format for Model Context Protocol (MCP) (#9650) --- .../roadmaps/frontend/content/mcp@XFy2gj7DmXeaCoc6MZo_j.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/data/roadmaps/frontend/content/mcp@XFy2gj7DmXeaCoc6MZo_j.md b/src/data/roadmaps/frontend/content/mcp@XFy2gj7DmXeaCoc6MZo_j.md index cfcf616ac..be4fbcd2f 100644 --- a/src/data/roadmaps/frontend/content/mcp@XFy2gj7DmXeaCoc6MZo_j.md +++ b/src/data/roadmaps/frontend/content/mcp@XFy2gj7DmXeaCoc6MZo_j.md @@ -1,4 +1,4 @@ -Model Context Protocol (MCP) +# Model Context Protocol (MCP) Model Context Protocol (MCP) is a rulebook that tells an AI agent how to pack background information before it sends a prompt to a language model. It lists what pieces go into the prompt—things like the system role, the user’s request, past memory, tool calls, or code snippets—and fixes their order. Clear tags mark each piece, so both humans and machines can see where one part ends and the next begins. Keeping the format steady cuts confusion, lets different tools work together, and makes it easier to test or swap models later. When agents follow MCP, the model gets a clean, complete prompt and can give better answers. @@ -9,4 +9,4 @@ Visit the following resources to learn more: - [@article@The Ultimate Guide to MCP](https://guangzhengli.com/blog/en/model-context-protocol) - [@article@A Clear Intro to MCP (Model Context Protocol) with Code Examples](https://towardsdatascience.com/clear-intro-to-mcp/) - [@article@Model Context Protocol (MCP): A Guide With Demo Project](https://www.datacamp.com/tutorial/mcp-model-context-protocol) -- [@course@MCP: Build Rich-Context AI Apps with Anthropic](https://www.deeplearning.ai/short-courses/mcp-build-rich-context-ai-apps-with-anthropic/) \ No newline at end of file +- [@course@MCP: Build Rich-Context AI Apps with Anthropic](https://www.deeplearning.ai/short-courses/mcp-build-rich-context-ai-apps-with-anthropic/)