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examples/agents/README.md

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@@ -61,37 +61,10 @@ sequenceDiagram
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## Installation and Usage
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### 1. Set up the Project Analyst Agent
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```bash
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# From the project-analyst directory
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cd project-analyst
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uv venv .venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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uv add --dev -e .
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# No need to run it directly - it will be started by the Personal Assistant
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```
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### 2. Set up the Personal Assistant Agent
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```bash
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# From the personal-assistant directory
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cd personal-assistant
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uv venv .venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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uv add --dev -e .
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# No need to run it directly - it will be started by the Chat CLI
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```
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### 3. Run the Chat CLI
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```bash
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# From the chat-cli directory
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cd chat-cli
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uv venv .venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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uv add --dev -e .
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uv run mcp-chat-cli
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uv pip install -e .
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cd examples/agents/chat-cli
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uv run mcp-chat-cli --log-level=DEBUG
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```
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This will start the entire agent chain. The Chat CLI will launch the Personal Assistant, which will in turn launch the Project Analyst.

examples/agents/chat-cli/pyproject.toml

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[project]
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name = "mcp_chat_cli"
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version = "0.1.0"
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authors = [
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{name = "MCP Team", email = "info@modelcontextprotocol.org"},
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]
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description = "Chat CLI for interacting with MCP agents"
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requires-python = ">=3.10"
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classifiers = [
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"Programming Language :: Python :: 3",
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"License :: OSI Approved :: MIT License",
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"Operating System :: OS Independent",
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]
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dependencies = [
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"mcp",
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"anyio",
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]
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dependencies = ["anyio>=4.5", "mcp"]
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[project.scripts]
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mcp-chat-cli = "mcp_chat_cli.cli:main"

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