modelscope-mcp-server


Namemodelscope-mcp-server JSON
Version 0.1.5 PyPI version JSON
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SummaryA Model Context Protocol (MCP) server that integrates with ModelScope's ecosystem.
upload_time2025-07-29 03:27:16
maintainerNone
docs_urlNone
authorNone
requires_python>=3.10
licenseApache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. 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keywords ai llm mcp model-context-protocol modelscope
VCS
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requirements No requirements were recorded.
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            # ModelScope MCP Server

[![PyPI - Version](https://img.shields.io/pypi/v/modelscope-mcp-server.svg)](https://pypi.org/project/modelscope-mcp-server)
[![Docker](https://img.shields.io/badge/docker-supported-blue?logo=docker)](https://github.com/modelscope/modelscope-mcp-server/blob/main/Dockerfile)
[![GitHub Container Registry](https://img.shields.io/badge/container-registry-blue?logo=github)](https://github.com/modelscope/modelscope-mcp-server/pkgs/container/modelscope-mcp-server)
[![License](https://img.shields.io/github/license/modelscope/modelscope-mcp-server.svg)](https://github.com/modelscope/modelscope-mcp-server/blob/main/LICENSE)

English | [δΈ­ζ–‡](README_zh-CN.md)

Empowers AI agents and chatbots with direct access to [ModelScope](https://modelscope.cn)'s rich ecosystem of AI resources. From generating images to discovering cutting-edge models, datasets, apps and research papers, this MCP server makes ModelScope's vast collection of tools and services accessible through simple conversational interactions.

## ✨ Features

- 🎨 **AI Image Generation** - Generate images from text prompts or transform existing images using AIGC models (supports both text-to-image and image-to-image generation)
- πŸ” **Resource Discovery** - Search and discover ModelScope resources including machine learning models, research papers, and MCP servers with advanced filtering options
- πŸ“‹ **Resource Details** _(Coming Soon)_ - Get comprehensive details for specific resources including model specifications, paper abstracts, and MCP server configurations
- πŸ“– **Documentation Search** _(Coming Soon)_ - Semantic search for ModelScope documentation and articles
- πŸš€ **Gradio API Integration** _(Coming Soon)_ - Invoke Gradio APIs exposed by any pre-configured ModelScope Studio (AI app)
- πŸ” **Context Information** - Access current operational context including authenticated user information and environment details

## πŸš€ Quick Start

### 1. Get Your API Token

1. Visit [ModelScope](https://modelscope.cn/home) and sign in to your account
2. Navigate to **[Home] β†’ [Access Tokens]** to retrieve or create your API token

> πŸ“– For detailed instructions, refer to the [ModelScope Token Documentation](https://modelscope.cn/docs/accounts/token)

### 2. Integration with MCP Clients

Add the following JSON configuration to your MCP client's configuration file:

```json
{
  "mcpServers": {
    "modelscope-mcp-server": {
      "command": "uvx",
      "args": ["modelscope-mcp-server"],
      "env": {
        "MODELSCOPE_API_TOKEN": "your-api-token"
      }
    }
  }
}
```

Or, you can use the pre-built Docker image:

```json
{
  "mcpServers": {
    "modelscope-mcp-server": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-e", "MODELSCOPE_API_TOKEN",
        "ghcr.io/modelscope/modelscope-mcp-server"
      ],
      "env": {
        "MODELSCOPE_API_TOKEN": "your-api-token"
      }
    }
  }
}
```

Refer to the [MCP JSON Configuration Standard](https://gofastmcp.com/integrations/mcp-json-configuration#mcp-json-configuration-standard) for more details.

This format is widely adopted across the MCP ecosystem:

- **Cherry Studio**: See [Cherry Studio MCP Configuration](https://docs.cherry-ai.com/advanced-basic/mcp/config)
- **Claude Desktop**: Uses `~/.claude/claude_desktop_config.json`
- **Cursor**: Uses `~/.cursor/mcp.json`
- **VS Code**: Uses workspace `.vscode/mcp.json`
- **Other clients**: Many MCP-compatible applications follow this standard

## πŸ› οΈ Development

### Environment Setup

1. **Clone and Setup**:

   ```bash
   git clone https://github.com/modelscope/modelscope-mcp-server.git
   cd modelscope-mcp-server
   uv sync
   ```

2. **Activate Environment** (or use your IDE):

   ```bash
   source .venv/bin/activate  # Linux/macOS
   ```

3. **Set Your API Token** (see Quick Start section for token setup):

   ```bash
   export MODELSCOPE_API_TOKEN="your-api-token"
   # Or create .env file: echo 'MODELSCOPE_API_TOKEN="your-api-token"' > .env
   ```

### Running the Demo Script

Run a quick demo to explore the server's capabilities:

```bash
uv run python demo.py
```

Use the `--full` flag for comprehensive feature demonstration:

```bash
uv run python demo.py --full
```

### Running the Server Locally

```bash
# Standard stdio transport (default)
uv run modelscope-mcp-server

# Streamable HTTP transport for web integration
uv run modelscope-mcp-server --transport http

# HTTP/SSE transport with custom port (default: 8000)
uv run modelscope-mcp-server --transport [http/sse] --port 8080
```

For HTTP/SSE mode, connect using a local URL in your MCP client configuration:

```json
{
  "mcpServers": {
    "modelscope-mcp-server": {
      "url": "http://127.0.0.1:8000/mcp/"
    }
  }
}
```

You can also debug the server using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector) tool:

```bash
# Run in UI mode with stdio transport (can switch to HTTP/SSE in the Web UI as needed)
npx @modelcontextprotocol/inspector uv run modelscope-mcp-server

# Run in CLI mode with HTTP transportt (can do operations across tools, resources, and prompts)
npx @modelcontextprotocol/inspector --cli http://127.0.0.1:8000/mcp/ --transport http --method tools/list
```

### Testing

```bash
# Run all tests
uv run pytest

# Run specific test file
uv run pytest tests/test_search_papers.py

# With coverage report
uv run pytest --cov=src --cov-report=html
```

## πŸ”„ Continuous Integration

This project uses GitHub Actions for automated CI/CD workflows that run on every push and pull request:

### Automated Checks

- **✨ [Lint](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/lint.yml)** - Code formatting, linting, and style checks using pre-commit hooks
- **πŸ§ͺ [Test](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/test.yml)** - Comprehensive testing across all supported Python versions
- **πŸ” [CodeQL](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/codeql.yml)** - Security vulnerability scanning and code quality analysis
- **πŸ”’ [Gitleaks](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/gitleaks.yml)** - Detecting secrets like passwords, API keys, and tokens

### Local Development Checks

Run the same checks locally before submitting PRs:

```bash
# Install and run pre-commit hooks
uv run pre-commit install
uv run pre-commit run --all-files

# Run tests
uv run pytest
```

Monitor CI status in the [Actions tab](https://github.com/modelscope/modelscope-mcp-server/actions).

## πŸ“¦ Release Management

This project uses GitHub Actions for automated release management. To create a new release:

1. **Update version** using the bump script:

   ```bash
   uv run python scripts/bump_version.py [patch|minor|major]
   # Or set specific version: uv run python scripts/bump_version.py set 1.2.3.dev1
   ```

2. **Commit and tag** (follow the script's output instructions):

   ```bash
   git add src/modelscope_mcp_server/_version.py
   git commit -m "chore: bump version to v{version}"
   git tag v{version} && git push origin v{version}
   ```

3. **Automated publishing** - GitHub Actions will automatically:
   - Create a new [GitHub Release](https://github.com/modelscope/modelscope-mcp-server/releases)
   - Publish package to [PyPI repository](https://pypi.org/project/modelscope-mcp-server/)
   - Build and push Docker image to [GitHub Container Registry](https://github.com/modelscope/modelscope-mcp-server/pkgs/container/modelscope-mcp-server)

## 🀝 Contributing

We welcome contributions! Please ensure your PRs:

- Include relevant tests and pass all CI checks
- Update documentation for new features
- Follow conventional commit format

## πŸ“š References

- **[Model Context Protocol](https://modelcontextprotocol.io/)** - Official MCP documentation
- **[FastMCP v2](https://github.com/jlowin/fastmcp)** - High-performance MCP framework
- **[MCP Example Servers](https://github.com/modelcontextprotocol/servers)** - Community server examples

## πŸ“œ License

This project is licensed under the [Apache License (Version 2.0)](LICENSE).

Raw data

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    "name": "modelscope-mcp-server",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.10",
    "maintainer_email": null,
    "keywords": "ai, llm, mcp, model-context-protocol, modelscope",
    "author": null,
    "author_email": "ModelScope Team <contact@modelscope.cn>",
    "download_url": "https://files.pythonhosted.org/packages/31/d7/921b98fa82505ab5e84d55f0b9e4d4d8e9cbfe423a323bb5b49389acf917/modelscope_mcp_server-0.1.5.tar.gz",
    "platform": null,
    "description": "# ModelScope MCP Server\n\n[![PyPI - Version](https://img.shields.io/pypi/v/modelscope-mcp-server.svg)](https://pypi.org/project/modelscope-mcp-server)\n[![Docker](https://img.shields.io/badge/docker-supported-blue?logo=docker)](https://github.com/modelscope/modelscope-mcp-server/blob/main/Dockerfile)\n[![GitHub Container Registry](https://img.shields.io/badge/container-registry-blue?logo=github)](https://github.com/modelscope/modelscope-mcp-server/pkgs/container/modelscope-mcp-server)\n[![License](https://img.shields.io/github/license/modelscope/modelscope-mcp-server.svg)](https://github.com/modelscope/modelscope-mcp-server/blob/main/LICENSE)\n\nEnglish | [\u4e2d\u6587](README_zh-CN.md)\n\nEmpowers AI agents and chatbots with direct access to [ModelScope](https://modelscope.cn)'s rich ecosystem of AI resources. From generating images to discovering cutting-edge models, datasets, apps and research papers, this MCP server makes ModelScope's vast collection of tools and services accessible through simple conversational interactions.\n\n## \u2728 Features\n\n- \ud83c\udfa8 **AI Image Generation** - Generate images from text prompts or transform existing images using AIGC models (supports both text-to-image and image-to-image generation)\n- \ud83d\udd0d **Resource Discovery** - Search and discover ModelScope resources including machine learning models, research papers, and MCP servers with advanced filtering options\n- \ud83d\udccb **Resource Details** _(Coming Soon)_ - Get comprehensive details for specific resources including model specifications, paper abstracts, and MCP server configurations\n- \ud83d\udcd6 **Documentation Search** _(Coming Soon)_ - Semantic search for ModelScope documentation and articles\n- \ud83d\ude80 **Gradio API Integration** _(Coming Soon)_ - Invoke Gradio APIs exposed by any pre-configured ModelScope Studio (AI app)\n- \ud83d\udd10 **Context Information** - Access current operational context including authenticated user information and environment details\n\n## \ud83d\ude80 Quick Start\n\n### 1. Get Your API Token\n\n1. Visit [ModelScope](https://modelscope.cn/home) and sign in to your account\n2. Navigate to **[Home] \u2192 [Access Tokens]** to retrieve or create your API token\n\n> \ud83d\udcd6 For detailed instructions, refer to the [ModelScope Token Documentation](https://modelscope.cn/docs/accounts/token)\n\n### 2. Integration with MCP Clients\n\nAdd the following JSON configuration to your MCP client's configuration file:\n\n```json\n{\n  \"mcpServers\": {\n    \"modelscope-mcp-server\": {\n      \"command\": \"uvx\",\n      \"args\": [\"modelscope-mcp-server\"],\n      \"env\": {\n        \"MODELSCOPE_API_TOKEN\": \"your-api-token\"\n      }\n    }\n  }\n}\n```\n\nOr, you can use the pre-built Docker image:\n\n```json\n{\n  \"mcpServers\": {\n    \"modelscope-mcp-server\": {\n      \"command\": \"docker\",\n      \"args\": [\n        \"run\", \"--rm\", \"-i\",\n        \"-e\", \"MODELSCOPE_API_TOKEN\",\n        \"ghcr.io/modelscope/modelscope-mcp-server\"\n      ],\n      \"env\": {\n        \"MODELSCOPE_API_TOKEN\": \"your-api-token\"\n      }\n    }\n  }\n}\n```\n\nRefer to the [MCP JSON Configuration Standard](https://gofastmcp.com/integrations/mcp-json-configuration#mcp-json-configuration-standard) for more details.\n\nThis format is widely adopted across the MCP ecosystem:\n\n- **Cherry Studio**: See [Cherry Studio MCP Configuration](https://docs.cherry-ai.com/advanced-basic/mcp/config)\n- **Claude Desktop**: Uses `~/.claude/claude_desktop_config.json`\n- **Cursor**: Uses `~/.cursor/mcp.json`\n- **VS Code**: Uses workspace `.vscode/mcp.json`\n- **Other clients**: Many MCP-compatible applications follow this standard\n\n## \ud83d\udee0\ufe0f Development\n\n### Environment Setup\n\n1. **Clone and Setup**:\n\n   ```bash\n   git clone https://github.com/modelscope/modelscope-mcp-server.git\n   cd modelscope-mcp-server\n   uv sync\n   ```\n\n2. **Activate Environment** (or use your IDE):\n\n   ```bash\n   source .venv/bin/activate  # Linux/macOS\n   ```\n\n3. **Set Your API Token** (see Quick Start section for token setup):\n\n   ```bash\n   export MODELSCOPE_API_TOKEN=\"your-api-token\"\n   # Or create .env file: echo 'MODELSCOPE_API_TOKEN=\"your-api-token\"' > .env\n   ```\n\n### Running the Demo Script\n\nRun a quick demo to explore the server's capabilities:\n\n```bash\nuv run python demo.py\n```\n\nUse the `--full` flag for comprehensive feature demonstration:\n\n```bash\nuv run python demo.py --full\n```\n\n### Running the Server Locally\n\n```bash\n# Standard stdio transport (default)\nuv run modelscope-mcp-server\n\n# Streamable HTTP transport for web integration\nuv run modelscope-mcp-server --transport http\n\n# HTTP/SSE transport with custom port (default: 8000)\nuv run modelscope-mcp-server --transport [http/sse] --port 8080\n```\n\nFor HTTP/SSE mode, connect using a local URL in your MCP client configuration:\n\n```json\n{\n  \"mcpServers\": {\n    \"modelscope-mcp-server\": {\n      \"url\": \"http://127.0.0.1:8000/mcp/\"\n    }\n  }\n}\n```\n\nYou can also debug the server using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector) tool:\n\n```bash\n# Run in UI mode with stdio transport (can switch to HTTP/SSE in the Web UI as needed)\nnpx @modelcontextprotocol/inspector uv run modelscope-mcp-server\n\n# Run in CLI mode with HTTP transportt (can do operations across tools, resources, and prompts)\nnpx @modelcontextprotocol/inspector --cli http://127.0.0.1:8000/mcp/ --transport http --method tools/list\n```\n\n### Testing\n\n```bash\n# Run all tests\nuv run pytest\n\n# Run specific test file\nuv run pytest tests/test_search_papers.py\n\n# With coverage report\nuv run pytest --cov=src --cov-report=html\n```\n\n## \ud83d\udd04 Continuous Integration\n\nThis project uses GitHub Actions for automated CI/CD workflows that run on every push and pull request:\n\n### Automated Checks\n\n- **\u2728 [Lint](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/lint.yml)** - Code formatting, linting, and style checks using pre-commit hooks\n- **\ud83e\uddea [Test](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/test.yml)** - Comprehensive testing across all supported Python versions\n- **\ud83d\udd0d [CodeQL](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/codeql.yml)** - Security vulnerability scanning and code quality analysis\n- **\ud83d\udd12 [Gitleaks](https://github.com/modelscope/modelscope-mcp-server/actions/workflows/gitleaks.yml)** - Detecting secrets like passwords, API keys, and tokens\n\n### Local Development Checks\n\nRun the same checks locally before submitting PRs:\n\n```bash\n# Install and run pre-commit hooks\nuv run pre-commit install\nuv run pre-commit run --all-files\n\n# Run tests\nuv run pytest\n```\n\nMonitor CI status in the [Actions tab](https://github.com/modelscope/modelscope-mcp-server/actions).\n\n## \ud83d\udce6 Release Management\n\nThis project uses GitHub Actions for automated release management. To create a new release:\n\n1. **Update version** using the bump script:\n\n   ```bash\n   uv run python scripts/bump_version.py [patch|minor|major]\n   # Or set specific version: uv run python scripts/bump_version.py set 1.2.3.dev1\n   ```\n\n2. **Commit and tag** (follow the script's output instructions):\n\n   ```bash\n   git add src/modelscope_mcp_server/_version.py\n   git commit -m \"chore: bump version to v{version}\"\n   git tag v{version} && git push origin v{version}\n   ```\n\n3. **Automated publishing** - GitHub Actions will automatically:\n   - Create a new [GitHub Release](https://github.com/modelscope/modelscope-mcp-server/releases)\n   - Publish package to [PyPI repository](https://pypi.org/project/modelscope-mcp-server/)\n   - Build and push Docker image to [GitHub Container Registry](https://github.com/modelscope/modelscope-mcp-server/pkgs/container/modelscope-mcp-server)\n\n## \ud83e\udd1d Contributing\n\nWe welcome contributions! Please ensure your PRs:\n\n- Include relevant tests and pass all CI checks\n- Update documentation for new features\n- Follow conventional commit format\n\n## \ud83d\udcda References\n\n- **[Model Context Protocol](https://modelcontextprotocol.io/)** - Official MCP documentation\n- **[FastMCP v2](https://github.com/jlowin/fastmcp)** - High-performance MCP framework\n- **[MCP Example Servers](https://github.com/modelcontextprotocol/servers)** - Community server examples\n\n## \ud83d\udcdc License\n\nThis project is licensed under the [Apache License (Version 2.0)](LICENSE).\n",
    "bugtrack_url": null,
    "license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/  TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION  1. Definitions.  \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.  \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.  \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.  \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License.  \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files.  \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.  \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).  \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. 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