thesis

Author: humanagent

THESIS.md

@@ -18,22 +18,12 @@ Under **Web4**, autonomous agents don’t rely exclusively on publicly indexed c
 
 Increasingly, organizations sell or lease access to real-time financial data, anonymized healthcare records, or specialized databases. These shared resources form a multi-agent ecosystem powered by advanced compute and specialized data—making airtight security paramount.
 
-## MCP from Anthropic
+### MCP from Anthropic
 
 ![1](/media/2.webp)
 
 MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.
 
-### [\*\*](https://modelcontextprotocol.io/introduction#why-mcp)Why MCP?\*\*
-
-MCP helps you build agents and complex workflows on top of LLMs. LLMs frequently need to integrate with data and tools, and MCP provides:
-
-- A growing list of pre-built integrations that your LLM can directly plug into
-- The flexibility to switch between LLM providers and vendors
-- Best practices for securing your data within your infrastructure
-
-### [\*\*](https://modelcontextprotocol.io/introduction#general-architecture)General architecture\*\*
-
 At its core, MCP follows a client-server architecture where a host application can connect to multiple servers:
 
 - **MCP Hosts**: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP