A
licenseNot graded
qualityD
maintenanceAn MCP server that enables AI assistants to access up-to-date documentation for Python libraries like LangChain, LlamaIndex, and OpenAI through dynamic fetching from official sources.
1
MIT
Atlas-Docs
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TDQS
A4.2/5.0
Scored across 5 tools
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: list_docs discovers documentation sets, get_docs_index provides an overview, get_docs_page retrieves specific content, get_docs_full gets everything, and search_docs finds keywords. The descriptions explicitly guide usage, making misselection unlikely.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case: list_docs, get_docs_index, get_docs_page, get_docs_full, and search_docs. The naming is predictable and readable, using clear verbs like 'get', 'list', and 'search' paired with descriptive nouns.
Tool Count5/5
With 5 tools, the count is well-scoped for a documentation server, covering discovery, navigation, retrieval, and search without being overwhelming. Each tool earns its place by addressing a specific need in the documentation workflow, from initial exploration to detailed content access.
Completeness5/5
The tool set provides complete coverage for documentation access: list_docs for discovery, get_docs_index for navigation, get_docs_page for targeted retrieval, get_docs_full for comprehensive content, and search_docs for keyword-based finding. There are no obvious gaps, and the descriptions guide agents through a logical workflow.
Maintenance
ActivityInactive
ResponsivenessNo issues