AI Analysis
The package appears safe with minimal risks identified. The primary concerns lie in the low maintainer engagement and poor metadata quality, which slightly elevate the metadata risk.
- Low network, shell, obfuscation, and credential risks.
- Metadata risk due to low maintainer engagement and poor metadata quality.
Per-check LLM notes
- Network: The use of httpx.AsyncClient suggests legitimate network requests, possibly for API interactions or data retrieval.
- Shell: No shell execution patterns detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
- Metadata: The package shows signs of low maintainer engagement and poor metadata quality, but there are no clear indicators of malicious intent.
Package Quality Overall: Medium (6.2/10)
Test suite present — 7 test file(s) found
Test runner config found: conftest.pyTest runner config found: pyproject.toml7 test file(s) detected (e.g. conftest.py)
Some documentation present
Documentation URL: "Documentation" -> https://docs.axio-agent.comDetailed PyPI description (4986 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
49 type-annotated function signatures detected in source
Active multi-contributor project
3 unique contributor(s) across 100 commits in mosquito/axio-agentSmall but multi-author team (3–4 contributors)
Heuristic Checks
Found 1 network call pattern(s)
ne: http_client = httpx.AsyncClient( headers=self._config.headers or None,
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Repository mosquito/axio-agent appears legitimate
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Develop a Python-based mini-application named 'AxioMCPManager' that leverages the 'axio-tools-mcp' package to manage and interact with MCP (Management Control Protocol) services provided by Axio. This application will serve as a command-line interface (CLI) tool for users to easily load, configure, and monitor MCP tools. The goal is to create a user-friendly and efficient way to manage Axio's MCP services without needing direct access to complex APIs or configurations. #### Features: 1. **Tool Loader**: Automatically load MCP tools using 'axio-tools-mcp'. Users should be able to specify which tools they want to load via command-line arguments. 2. **Configuration Manager**: Allow users to set up configurations for the loaded tools through a simple CLI interface. These configurations could include settings like API endpoints, authentication tokens, etc. 3. **Status Monitor**: Provide real-time status updates for each loaded tool. Users should be able to see if their tools are running successfully or if there are any issues. 4. **Error Handling**: Implement robust error handling to ensure that any issues encountered during tool loading or configuration are clearly communicated to the user. 5. **Help Documentation**: Include a help menu that provides instructions on how to use each feature of the application. #### Steps to Develop the Application: 1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with 'axio-tools-mcp'. 2. **Design the CLI Interface**: Design a user-friendly CLI interface where users can input commands to load tools, configure settings, and check statuses. 3. **Implement Tool Loading**: Use 'axio-tools-mcp' to implement the functionality for loading MCP tools. This involves understanding the package's API and how to call its methods from within your application. 4. **Add Configuration Management**: Develop a module within your application that allows users to set up configurations for the loaded tools. This should include options for setting API keys, specifying endpoints, etc. 5. **Integrate Status Monitoring**: Incorporate real-time monitoring of the loaded tools. Display the status of each tool in the CLI output. 6. **Enhance with Error Handling**: Add comprehensive error handling to manage exceptions and provide meaningful feedback to the user. 7. **Create Help Documentation**: Finally, create a help menu that explains how to use each feature of the application effectively. 8. **Testing**: Test the application thoroughly to ensure all features work as expected. 9. **Deployment**: Prepare the application for deployment. Consider packaging it as a standalone executable or as a package that can be installed via pip. This project not only showcases your ability to work with third-party Python packages but also demonstrates your proficiency in developing command-line applications and managing configurations.
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