Open Issues Need Help
View All on GitHubAI Summary: The global HTTP client in `server.py` is never properly closed, leading to connection leaks, memory issues, and potential connection timeouts. The `BeninPortalClient` has a `close()` method that is never invoked, and the proposed solution involves using FastMCP's `@lifespan` mechanism to manage the client's lifecycle.
AI Summary: This issue addresses a security vulnerability in the project's dependencies. The current version constraint for `fastmcp` is too permissive, allowing installation of future major versions that could introduce breaking changes. The proposed solution is to update the constraint to `fastmcp>=3.0.0,<4.0.0` to ensure compatibility and prevent potential security risks.
AI Summary: This issue proposes an enhancement to the `download_dataset` tool to implement a hybrid download method. Currently, it always returns content as base64, leading to unreadable interfaces, excessive file sizes, and potential timeouts for large files. The proposed solution introduces an 'auto' method that intelligently chooses between returning a direct URL for files over 1MB or HTML pages, and base64 encoding for smaller files, improving performance and usability.
AI Summary: The `preview_dataset` tool currently does not support HTML resources, preventing users from previewing data contained within HTML files. The issue proposes adding a dedicated HTML handler to extract structured data, such as tables, from HTML content.
AI Summary: This issue proposes adding client-side pagination to the `get_all_datasets()` and `search_datasets()` functions to handle large result sets. The solution involves introducing an `offset` parameter to `get_all_datasets()`, creating an iterator for seamless traversal of all datasets, and updating the `search_datasets()` tool to support pagination.
AI Summary: This issue identifies that the `skill.md` documentation file is missing entries for two crucial MCP tools: `preview_dataset` and `download_dataset`. The goal is to add comprehensive documentation for these tools, including their parameters, return values, supported formats, use cases, and example workflows, to improve the usability for AI agents.