Provides comprehensive corporate credit data for AI agents, including a Python SDK, LangChain tools, and an MCP server.
Sponsored
Equity data is readily available, but corporate credit data is often fragmented across SEC filings, making it difficult for AI agents to perform complex financial analysis. DebtStack addresses this by extracting, normalizing, and serving crucial corporate credit data—such as debt structures, guarantor chains, and covenant details—through a high-speed API optimized for AI agent consumption. This enables cross-company credit queries, pre-built entity relationships, and rapid response times for in-depth credit analysis.
主な機能
01Cross-Company Credit Queries for screening by leverage, coverage, or maturity risk
02Integrations for LangChain and MCP Server (Claude Desktop, Claude Code, Cursor)
03Agent-Ready Speed with sub-100ms response times for chained queries
04Pre-Built Entity Relationships mapping guarantor chains and corporate hierarchies
050 GitHub stars
06Comprehensive Coverage of companies, entities, debt instruments, pricing, and SEC filing sections
ユースケース
01Screening for high-leverage or distressed companies within specific sectors
02Analyzing guarantor chains and structural subordination for corporate bonds
03Searching for specific covenant language in credit agreements and indentures
