How do I switch between Professional Plan and API usage?
Use normal chat for Professional Plan. Prefix any message with `@claude-api` to route the request through the MCP server and use your API key and credits.
@ptitiwat2543
Basic information
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No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
This project develops an MCP (Machine Communication Protocol) server that integrates Claude Desktop with the Claude API. It allows users to access advanced features such as system prompts, conversation management, and longer context windows directly from Claude Desktop.
Clone the repository, install dependencies with pip install -r requirements.txt, copy .env.example to .env and set your ANTHROPIC_API_KEY. Then configure Claude Desktop by editing claude_desktop_config.json (located at ~/Library/Application Support/Claude/ on macOS or %APPDATA%\Claude\ on Windows) with the server path. Use @claude-api in chat to invoke API tools (e.g., @claude-api query_claude prompt="What is the capital of France?").
Use normal chat for Professional Plan. Prefix any message with `@claude-api` to route the request through the MCP server and use your API key and credits.
The server supports Claude 3 Opus, Claude 3 Sonnet, Claude 3 Haiku, and Claude 3.5 Sonnet. Use `@claude-api list_available_models` to see all available models.
Use `@claude-api query_claude` with a `conversation_id` parameter to track a thread. Retrieve history with `get_conversation_history`, list all conversations with `list_conversations`, and clear one with `clear_conversation`.
Yes, API calls use your Anthropic API credits and may incur charges. It is recommended to use the Professional Plan for general inquiries and `@claude-api` only when you need advanced features.
Conversation histories are managed server‑side by the MCP server; no data is stored outside your local environment unless you configure otherwise. The server itself runs locally.
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