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https://github.com/modelscope/FunASR.git
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Add Glama metadata for MCP server (#3076)
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@@ -25,6 +25,8 @@ docker run --rm -i \
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When submitting this server to MCP directories such as Glama, use this folder as
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the Docker build context so the container entrypoint runs `funasr_mcp.py`.
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The `glama.json` file in this directory declares the MCP server command and
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metadata for directory scanners.
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### 3. Configure your AI tool
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@@ -0,0 +1,19 @@
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{
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"$schema": "https://glama.ai/api/mcp/v1/schemas/glama.json",
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"name": "funasr",
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"display_name": "FunASR MCP Server",
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"description": "Local speech recognition MCP server powered by FunASR and SenseVoice. It exposes a transcribe_audio tool for privacy-friendly audio transcription from local files.",
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"repository": "https://github.com/modelscope/FunASR",
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"license": "MIT",
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"runtime": "python",
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"tags": ["speech-to-text", "asr", "audio", "funasr", "sensevoice", "local", "mcp"],
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"mcpServers": {
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"funasr": {
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"command": "python",
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"args": ["/app/funasr_mcp.py"],
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"env": {
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"FUNASR_DEVICE": "cpu"
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}
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}
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}
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}
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@@ -1,3 +1,4 @@
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import json
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from pathlib import Path
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@@ -12,3 +13,16 @@ def test_mcp_server_example_has_glama_ready_dockerfile():
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assert "funasr" in dockerfile_text
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assert "COPY funasr_mcp.py /app/funasr_mcp.py" in dockerfile_text
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assert 'CMD ["python", "/app/funasr_mcp.py"]' in dockerfile_text
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def test_mcp_server_example_has_glama_metadata():
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example_dir = Path(__file__).resolve().parents[1] / "examples" / "mcp_server"
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metadata_path = example_dir / "glama.json"
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metadata = json.loads(metadata_path.read_text())
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assert metadata["repository"] == "https://github.com/modelscope/FunASR"
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assert metadata["runtime"] == "python"
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assert metadata["license"] == "MIT"
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assert metadata["mcpServers"]["funasr"]["command"] == "python"
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assert metadata["mcpServers"]["funasr"]["args"] == ["/app/funasr_mcp.py"]
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