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title: Best MCP posts — November 2025 | daily.dev
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# Best of MCP — November 2025

1. 1  
[](https://daily.dev/posts/anthropic-admits-that-mcp-sucks-cc8atbcq1 "Anthropic admits that MCP sucks")  
Video  
![Avatar of t3dotgg](https://media.daily.dev/image/upload/s--UmX7IyU3--/f_auto/v1704628081/logos/t3dotgg.jpg)Theo - t3․gg · 43w  
Anthropic admits that MCP sucks  
Anthropic published guidance showing that code execution is 98.7% more efficient than their Model Context Protocol (MCP) specification for AI agents. The article demonstrates how writing code to interact with MCP servers reduces token usage from 150,000 to 2,000 tokens by avoiding context window bloat from tool definitions and intermediate results. This approach enables on-demand tool loading, data filtering before reaching the model, and better privacy controls, though it requires secure sandboxed execution environments.  
38  
2
2. 2  
[](https://daily.dev/posts/3-mcp-servers-you-should-be-using-safely--hggv2c6n3 "3 MCP servers you should be using (safely)")  
Article  
![Avatar of rhdev](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/2a8895f3216c4900bdc455585a4ad3e4)Red Hat Developer · 44w  
3 MCP servers you should be using (safely)  
Model Context Protocol (MCP) enables AI models to interact with developer tools and services through standardized servers. Three essential MCP servers are highlighted: Kubernetes for cluster management and diagnostics, Context7 for accessing up-to-date technical documentation, and GitHub for repository interactions. Each server requires careful security configuration, including read-only defaults, human approval for write operations, and minimal access tokens to prevent data exfiltration through prompt injection attacks.  
37  
3
3. 3  
[](https://daily.dev/posts/agent-protocol-landscape-bvbbuo3wf "Agent Protocol Landscape")  
Article  
![Avatar of dailydoseofds](https://media.daily.dev/image/upload/s--4IHQgTOw--/f_auto/v1710503712/logos/dailydoseofds)Daily Dose of Data Science | Avi Chawla | Substack · 43w  
Agent Protocol Landscape  
Three emerging protocols are standardizing the fragmented AI agent ecosystem: AG-UI for agent-user interaction in frontends, MCP (Model Context Protocol) for connecting agents to tools and data, and A2A for multi-agent coordination. These protocols work as complementary layers rather than competing standards, with frameworks like CopilotKit providing a unified interface to build with all three. The convergence enables seamless integration between agentic backends, frontends, tools, and multi-agent systems through open-source implementations.  
19

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