DADL is a declarative YAML format that lets a single runtime handle many REST API tools for LLM agents, cutting tool advertisement context cost by 142x from 142,000 to 1,000 tokens on a catalog of 1,833 definitions.
ToolFactory: Automating tool generation by leveraging LLM to understand REST API documentations
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
First large-scale empirical analysis of MCP server construction shows predominant REST wrapping with low operation exposure, plus an AutoMCP pipeline that improves automated generation success and reduces tool complexity.
NaviAgent decouples task planning from tool execution via a Tool World Navigation Model graph to improve scalability and success rates in LLM agents handling large tool ecosystems.
HarnessAPI derives streaming HTTP endpoints, OpenAPI UI, and MCP tools from a single handler.py plus Pydantic schemas, cutting framework boilerplate by 74%.
citing papers explorer
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DADL: A Declarative Description Language for Enterprise Tool Libraries in LLM Agent Systems
DADL is a declarative YAML format that lets a single runtime handle many REST API tools for LLM agents, cutting tool advertisement context cost by 142x from 142,000 to 1,000 tokens on a catalog of 1,833 definitions.
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From REST to MCP: An Empirical Study of API Wrapping and Automated Server Generation for LLM Agents
First large-scale empirical analysis of MCP server construction shows predominant REST wrapping with low operation exposure, plus an AutoMCP pipeline that improves automated generation success and reduces tool complexity.
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NaviAgent: Bilevel Planning on Tool Navigation Graph for Large-Scale Orchestration
NaviAgent decouples task planning from tool execution via a Tool World Navigation Model graph to improve scalability and success rates in LLM agents handling large tool ecosystems.
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HarnessAPI: A Skill-First Framework for Unified Streaming APIs and MCP Tools
HarnessAPI derives streaming HTTP endpoints, OpenAPI UI, and MCP tools from a single handler.py plus Pydantic schemas, cutting framework boilerplate by 74%.