mcpbeat

DebtStack.ai MCP Server

io.github.marcellusgreen/debtstack-ai
local only

DebtStack.ai runs on your own machine — the client starts it, so there is no endpoint to ping. 87 installs a week from pypi.

Corporate credit data API for AI agents — bonds, leverage, guarantors, SEC filings

Installs per day peak 59 · avg 15 · +19% w/w
a month agotoday
87
Installs / week
pypi · debtstack-ai
Stars
on GitHub
Last commit
0 releases in 90 days
License
language unknown

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add debtstack-ai -- uvx debtstack-ai
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "debtstack-ai": {
      "args": [
        "debtstack-ai"
      ],
      "command": "uvx"
    }
  }
}
~/.codex/config.toml
[mcp_servers.debtstack-ai]
command = "uvx"
args = ["debtstack-ai"]
.cursor/mcp.json
{
  "mcpServers": {
    "debtstack-ai": {
      "args": [
        "debtstack-ai"
      ],
      "command": "uvx"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "debtstack-ai": {
      "args": [
        "debtstack-ai"
      ],
      "command": "uvx"
    }
  }
}

DebtStack.ai — questions

Answers built from our own checks of this server.

Why is there no uptime for DebtStack.ai?
DebtStack.ai runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package debtstack-ai was installed 87 times last week.
How do I connect DebtStack.ai?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls debtstack-ai straight from pypi; nothing to host, nothing to sign up for.
How many people use DebtStack.ai?
The pypi package debtstack-ai was installed 87 times in the last week. Week over week that is +19%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.