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You can implement an MCP tool once and connect it to multiple compatible AI host applications. This tutorial builds a small Python server, checks its tool with the MCP Inspector, then configures Claude Code, Cursor and VS Code to launch the same server. Each host has its own MCP client and configuration; the tool behavior stays in the shared server.
What MCP does—and what it does not do
Model Context Protocol (MCP) is a protocol that lets a host application connect to a server providing capabilities such as tools, resources and prompts. For a tool call, the client discovers the server’s available tools and input schemas, then invokes a selected tool by name with arguments. The agent or model chooses when to request a call; the host’s MCP client mediates the exchange with the server. MCP defines that connection, not the model’s decision-making loop. The Python SDK overview and TypeScript SDK overview describe the server and client roles.
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In this example, “three agents” means three separate host applications—Claude Code, Cursor and VS Code—that can each use an MCP server. They are not three agents running inside the server. The server exposes one tool; each host connects to it using its own setup.
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This tutorial uses the Python SDK’s v2 documentation and a local stdio connection. The SDK overview lists Python 3.10 or later as a requirement. If you prefer TypeScript, its v2 server quickstart requires Node.js 20 or later; the TypeScript SDK overview also lists Bun and Deno as supported runtimes. Follow the relevant SDK’s current installation and package instructions rather than mixing setup commands between languages. Python SDK overview; TypeScript SDK overview; TypeScript server quickstart.
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| Connection choice | How it works | Use it when |
|---|---|---|
| stdio | The host launches the server as a local child process and exchanges protocol messages with it. | The host and server run on the same machine, and the host can access the server’s files and runtime. |
| Streamable HTTP | The server is reachable through a URL, and clients connect over HTTP. | Clients need to reach a server that is not launched as a local process, such as a remotely deployed service. |
The Python SDK documents both patterns; it does not prescribe one transport as best for every deployment. Remote access also requires deployment and access-control decisions beyond the local tutorial. See the Python SDK client reference and host integration guide.
Build a small Python tool server
Install and initialize the Python SDK according to its getting-started guide. The SDK’s examples use typed Python functions to define tool inputs. A minimal tool can add two numbers; the important design choices are a clear name, a useful description and typed arguments that make the expected input explicit.
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from mcp.server.fastmcp import FastMCP
mcp = FastMCP("shared-tools")
@mcp.tool()
def add(a: int, b: int) -> int:
"""Add two integers and return the total."""
return a + b
if __name__ == "__main__":
mcp.run()Save the file as server.py in your project. The Python quickstart explains that function type hints define the tool argument schema. Its documented example returns 3 when the tool is called with 1 and 2; that is the SDK’s example output, not a separate test of this article’s file.
Inspect the tool before connecting hosts
Run the Inspector using the command documented in the Python SDK quickstart:
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uv run mcp dev server.pyThe MCP Inspector opens an interface where you can connect to the local server, see the registered tool and call it with arguments. The Python documentation notes that the Inspector is a Node.js application and requires npx to be available on your PATH. If it does not start, check that prerequisite and confirm that the command runs from the directory containing server.py. Python SDK getting started.
Connect Claude Code, Cursor and VS Code to the same server
Each host needs its own MCP entry, but all three entries should launch the same Python file with the same environment. The Python SDK’s host integration guide documents setup for Claude Code, Cursor, VS Code and Claude Desktop. The following are the relevant configuration locations and approaches for the three hosts used here:
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| Host | Setup documented by the Python SDK | What to configure |
|---|---|---|
| Claude Code | Use the Claude Code CLI configuration approach in the SDK guide. | Register a stdio server command that runs server.py with the Python environment used by the project. |
| Cursor | Configure the project’s .cursor/mcp.json. |
Add a stdio server entry pointing to the same command and script path. |
| VS Code | Configure the project’s .vscode/mcp.json. |
Add a stdio server entry pointing to the same command and script path. |
Use the exact configuration shape and current host-specific commands shown in the guide; application labels and supported options can change. Where a host requires an absolute executable or script path, supply one rather than relying on the host’s working directory. Restart or reload the host after editing configuration so it starts the server with the new settings. Keep protocol output on stdout reserved for MCP messages: send diagnostic logging to stderr so it does not interfere with communication.
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What changes if you write an MCP client yourself?
A host application already supplies an MCP client. If you instead build your own client, the TypeScript quickstart describes the basic sequence: connect a Client using a transport, call listTools, provide those tool definitions to a model, and pass the model-selected tool name and arguments to callTool. The client handles MCP communication; your application is responsible for the model interaction and the loop that decides when to call a tool. See the TypeScript client quickstart.
When one shared server makes sense
- Local development: Keep the server on your machine and use stdio when each host can launch the same project command.
- Shared access: Use Streamable HTTP when clients need to connect by URL rather than start a local process. Plan deployment and access controls as part of making it reachable.
- Multiple tools: Add tools to the same server when they belong together and have compatible runtime and access needs. Hosts can discover the server’s available tools rather than needing a separate implementation in each host.
- Different host needs: Keep host-specific behavior in each host’s configuration or application. A shared server does not make the host applications interchangeable.
The Python SDK describes v2 as its current stable release line and keeps v1 documentation separately; it instructs v1 users to pin below v2. The TypeScript v2 documentation identifies its release line as implementing the 2026-07-28 specification. SDKs and host integrations evolve, so check the current guides for package names, version requirements and configuration details before adopting them. Python SDK overview; TypeScript SDK v2 overview.
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