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Add 4 MCP Resources for direct data lookups:
- package://{registry}/{name} - Package info from npm/pypi/crates/go
- github://{owner}/{repo} - Repository information
- status://{service} - Service health status
- changelog://{registry}/{package} - Package changelogs
Add 5 MCP Prompts for reusable workflows:
- research_package - Comprehensive package evaluation
- debug_error - Error debugging assistance
- compare_technologies - Technology comparison
- evaluate_repository - GitHub repo evaluation
- check_service_health - Multi-service status check
Resources enable direct data access without tool calls.
Prompts provide pre-built workflows that guide AI assistants.
Copy file name to clipboardExpand all lines: pyproject.toml
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[project]
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name = "web-research-assistant"
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version = "0.2.0"
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description = "Comprehensive MCP server for web research with 13 tools: search, crawl, package info, GitHub stats, error translation, API docs discovery, and more."
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version = "0.3.0"
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description = "Comprehensive MCP server for web research with 13 tools, 4 resources, and 5 prompts: search, crawl, package info, GitHub stats, error translation, API docs discovery, and more."
3. **Security**: Any known vulnerabilities or security concerns?
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4. **Dependencies**: How many dependencies does it have? Any concerns?
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5. **Alternatives**: What are the main alternatives and how does this compare?
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6. **Recommendation**: Should I use this package? Why or why not?
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Use the package://{registry}/{package} resource to get the package information, then search for additional context about alternatives and community sentiment."""
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@mcp.prompt()
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defdebug_error(
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error_message: str,
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language: str="",
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framework: str="",
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) ->str:
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"""
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Generate a prompt for debugging an error message.
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Use this when you encounter an error and want help understanding and fixing it.
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