38 lines
1.7 KiB
Markdown
38 lines
1.7 KiB
Markdown
# An LLM-Powered Chatbot MCP Client written in Rust
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An interactive chatbot MCP client: it launches an MCP server over stdio, lists its tools, and hands them to Claude, which can call them while answering your questions.
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This example accompanies the [Build an MCP client](https://modelcontextprotocol.io/docs/develop/build-client) tutorial.
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## Prerequisites
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- Rust (stable) and Cargo
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- An [Anthropic API key](https://console.anthropic.com/) (optional — see below)
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## Setup
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Export your API key, or put it in a `.env` file in this directory (the `.env` file is optional):
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```bash
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export ANTHROPIC_API_KEY=your-api-key-here
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```
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## Run the client
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Pass the command that starts the server — a binary or a script — after `--`:
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```bash
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cargo run -- ../weather-server-rust/target/release/weather
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```
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(Build the server first with `cargo build --release` in its directory.)
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Type a question (for example, "What's the weather in Sacramento?") and Claude answers using the server's tools. Type `quit` to exit.
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Without an `ANTHROPIC_API_KEY`, the client still connects, prints the server's tools, and exits — useful for verifying the MCP wiring without credentials.
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## Structured content
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rmcp does not validate tool output, so this client compiles each declared `outputSchema` at connect time and checks results against it — the spec's client-side SHOULD. It uses the [`jsonschema`](https://docs.rs/jsonschema) crate, which rmcp's own documentation recommends.
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The two channels go to different readers: `content` is forwarded to the model, while `structured_content` is used as data — the client counts the items it returns. See [Structured Content](https://modelcontextprotocol.io/specification/2026-07-28/server/tools#structured-content).
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