DebtStack.Ai
Let an agent pull corporate credit facts—bonds, leverage, guarantors, and SEC filings—while researching B2B or fintech ideas.
Overview
io.github.marcellusgreen/debtstack-ai is a MCP server for the Idea phase that lets agents query corporate credit data including bonds, leverage, guarantors, and SEC filings.
What is this MCP server?
- Corporate credit data API exposed as MCP for AI agents
- Data themes: bonds, leverage, guarantors, SEC filings
- PyPI package debtstack-ai with stdio transport (DebtStack.ai)
- Server version 0.1.5 in MCP registry metadata
- Suited to credit-analysis copilots rather than retail budgeting apps
- Advertised data domains: bonds, leverage, guarantors, SEC filings
- PyPI identifier debtstack-ai, stdio transport
What problem does it solve?
Founders researching credit or capital-structure products struggle to pipe reliable corporate bond and filing data into agent workflows without custom API glue.
Who is it for?
Indie builders prototyping credit research agents, due-diligence assistants, or fintech MVPs grounded in public company obligations.
Skip if: Consumer debt payoff apps, live trading execution, or teams that cannot use external finance APIs.
What do I get? / Deliverables
After registration, your agent can call DebtStack.ai credit tools during research sessions instead of hand-building SEC and leverage data fetchers.
- Agent-callable corporate credit and filing queries via MCP
- Faster issuer and leverage research loops during ideation
- Structured data hooks for downstream Build-phase dashboards or APIs
Recommended MCP Servers
Journey fit
Credit and filing research happens earliest when validating markets, counterparties, or data products, which maps to Idea research. Research subphase is where builders gather external datasets before committing to a build or integration contract.
How it compares
Corporate credit data MCP integration, not a spreadsheet plugin or accounting ledger.
Common Questions / FAQ
Who is io.github.marcellusgreen/debtstack-ai for?
Solo builders and analysts using AI agents who need corporate credit and SEC-oriented datasets for research or fintech prototypes.
When should I use io.github.marcellusgreen/debtstack-ai?
Use it during Idea research when evaluating issuers, leverage, guarantors, or filing-backed narratives before you hard-code a data pipeline.
How do I add io.github.marcellusgreen/debtstack-ai to my agent?
Install the PyPI package debtstack-ai, add a stdio MCP server block in Claude Code or Cursor, configure any DebtStack API credentials required by the upstream service, then invoke credit tools from chat.