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15 changes: 15 additions & 0 deletions
examples/mcp/CMakeLists.txt
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| set(TARGET whisper-mcp-server) | ||
| add_executable(${TARGET} mcp-server.cpp stdio-transport.cpp mcp-handler.cpp) | ||
| target_include_directories(${TARGET} PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}) | ||
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| set(DEMO_TARGET mcp-demo) | ||
| add_executable(${DEMO_TARGET} mcp-demo.cpp stdio-client.cpp) | ||
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| include(DefaultTargetOptions) | ||
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| target_link_libraries(${TARGET} PRIVATE common json_cpp whisper ${CMAKE_THREAD_LIBS_INIT}) | ||
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| # mcp_client only needs json_cpp and threading not whisper. | ||
| target_link_libraries(${DEMO_TARGET} PRIVATE json_cpp ${CMAKE_THREAD_LIBS_INIT}) | ||
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| install(TARGETS ${TARGET} ${DEMO_TARGET} RUNTIME) |
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examples/mcp/README.md
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| # whisper.cpp/examples/mcp | ||
| This directory contains an example of using the Model Context Protocol (MCP) with `whisper.cpp`. The transport | ||
| used in this example is the simple input/output (stdin/stdout) transport. When using the input/output transport, | ||
| the client is responsible for starting the server as a child process and the communication is done by reading | ||
| and writing data to stardard in/out. | ||
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| ## Usage | ||
| The stdio client demo can be run using the following command: | ||
| ``` | ||
| ./build/bin/mcp-demo | ||
| ``` | ||
| This will initalize the server using the [initialization] lifecycle phase. | ||
| Following that the client will send a request for the list of tools ([tools/list]) that the server supports. | ||
| It will then send a request to transcribe an audio file. | ||
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| ### Claude.ai Desktop integration | ||
| The Whisper.cpp MCP server can be integrated with the Claude.ai Desktop application. | ||
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| This requires adding a MCP server configuration to the Claude.ai Desktop: | ||
| ```console | ||
| $ cat ~/Library/Application\ Support/Claude/claude_desktop_config.json | ||
| { | ||
| "mcpServers": { | ||
| "whisper": { | ||
| "command": "/Users/danbev/work/ai/whisper.cpp/build/bin/whisper-mcp-server", | ||
| "args": [ | ||
| "--model", | ||
| "/Users/danbev/work/ai/whisper.cpp/models/ggml-base.en.bin" | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| ``` | ||
| Update the above paths to match your local system. And then restart the Claude.ai Desktop application. | ||
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| After that, clicking on "Connect apps" should show the following: | ||
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|  | ||
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| And clicking on `[...]` should show the tools available: | ||
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|  | ||
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| We should then be able to transribe an audio file by using a prompt like this: | ||
| ```console | ||
| Can you transcribe the audio file at /Users/danbev/work/ai/whisper.cpp/samples/jfk.wav? | ||
| ``` | ||
| And this will then prompt for accepting to run the transcription tool: | ||
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|  | ||
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| And this should result in a successful transcription: | ||
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|  | ||
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| [initialization]: https://modelcontextprotocol.io/specification/2025-03-26/basic/lifecycle#initialization | ||
| [tools/list]: https://modelcontextprotocol.io/specification/2025-03-26/server/tools#listing-tools |
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examples/mcp/mcp-demo.cpp
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| #include "stdio-client.hpp" | ||
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| #include <string> | ||
| #include <iostream> | ||
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| void pretty_print_json(const json & j) { | ||
| std::cout << j.dump(2) << std::endl; | ||
| } | ||
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| int main(int argc, char ** argv) { | ||
| std::string server_command = "build/bin/whisper-mcp-server"; | ||
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| if (argc > 1) { | ||
| server_command = argv[1]; | ||
| } | ||
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| printf("Starting MCP Demo\n"); | ||
| printf("Server command: %s\n", server_command.c_str()); | ||
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| try { | ||
| mcp::StdioClient client; | ||
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| // Start the server | ||
| printf("Starting server...\n"); | ||
| if (!client.start_server(server_command)) { | ||
| fprintf(stderr, "Failed to start server\n"); | ||
| return 1; | ||
| } | ||
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| if (!client.wait_for_server_ready(2000)) { | ||
| fprintf(stderr, "Server failed to start within timeout\n"); | ||
| return 1; | ||
| } | ||
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| client.read_server_logs(); | ||
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| // Initialize | ||
| printf("Initializing...\n"); | ||
| json init_response = client.initialize("mcp-demo-client", "1.0.0"); | ||
| printf("Initialize response:\n"); | ||
| pretty_print_json(init_response); | ||
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| if (init_response.contains("error")) { | ||
| fprintf(stderr, "Initialization failed!\n"); | ||
| return 1; | ||
| } | ||
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| // Send initialized notification | ||
| printf("Sending initialized notification...\n"); | ||
| client.send_initialized(); | ||
| client.read_server_logs(); | ||
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| // List tools | ||
| printf("Listing tools...\n"); | ||
| json tools_response = client.list_tools(); | ||
| printf("Tools list response:\n"); | ||
| pretty_print_json(tools_response); | ||
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| // Call transcribe tool | ||
| printf("Calling transcribe tool...\n"); | ||
| json transcribe_args = { | ||
| {"file", "samples/jfk.wav"} | ||
| }; | ||
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| json transcribe_response = client.call_tool("transcribe", transcribe_args); | ||
| printf("Transcribe response:\n"); | ||
| pretty_print_json(transcribe_response); | ||
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| // Call model info tool | ||
| printf("Calling model info tool...\n"); | ||
| json model_info_response = client.call_tool("model_info", json::object()); | ||
| printf("Model info response:\n"); | ||
| pretty_print_json(model_info_response); | ||
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| // Final logs | ||
| printf("Final server logs:\n"); | ||
| client.read_server_logs(); | ||
| } catch (const std::exception & e) { | ||
| fprintf(stderr, "Exception: %s\n", e.what()); | ||
| return 1; | ||
| } | ||
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| return 0; | ||
| } |
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