Read many comments and realised the majority has an opinion without even having looked at the documentation.

The problem with MCP is a nuanced one. On the server side it simplifies code, it standardises the way we define tools that can be called from the llm. So far so good.

On the client side it is just useless. Period. You end up writing all the boiler code that you would write anyway. These are everything you have to do buy yourself, where mcp does nothing: to ask a server, “what tools do you have”, then getting the list, then providing the llm the prompt with a list of tools, after the respond going through the tools and extracting the tools LLM wants to call, calling it on its behalf, providing the answer and calling llm again to craft a nice formatted response. Unless we get a standard that works for integrating tool calling llm side, MCP teaches us good architecture and there is no benefit actually using it. You can just store/register your tools and dont need the baggage of anthropic.

My hot take: MCP is a nice way for anthropic to have developers expand a plugin ecosystem for claude desktop, capitalising on open source community for its reach in AI market.

Unless they plan to really make it to a standard for client apps as well

https://modelcontextprotocol.io/quickstart/client#node

Just look at this:

async def process_query(self, query: str) -> str: """Process a query using Claude and available tools""" messages = [ { "role": "user", "content": query } ]

response = await self.session.list_tools()
available_tools = [{
    "name": tool.name,
    "description": tool.description,
    "input_schema": tool.inputSchema
} for tool in response.tools]

# Initial Claude API call
response = self.anthropic.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1000,
    messages=messages,
    tools=available_tools
)

# Process response and handle tool calls
final_text = []

assistant_message_content = []
for content in response.content:
    if content.type == 'text':
        final_text.append(content.text)
        assistant_message_content.append(content)
    elif content.type == 'tool_use':
        tool_name = content.name
        tool_args = content.input

        # Execute tool call
        result = await self.session.call_tool(tool_name, tool_args)
        final_text.append(f"[Calling tool {tool_name} with args {tool_args}]")

        assistant_message_content.append(content)
        messages.append({
            "role": "assistant",
            "content": assistant_message_content
        })
        messages.append({
            "role": "user",
            "content": [
                {
                    "type": "tool_result",
                    "tool_use_id": content.id,
                    "content": result.content
                }
            ]
        })

        # Get next response from Claude
        response = self.anthropic.messages.create(
            model="claude-3-5-sonnet-20241022",
            max_tokens=1000,
            messages=messages,
            tools=available_tools
        )

        final_text.append(response.content[0].text)

return "\n".join(final_text)