# Drillr

> Use this tool when you need to access comprehensive financial research data, including structured financials, SEC filings, and market data, to inform investment decisions or business strategies. Drillr solves problems related to financial data aggregation, search, and analysis, providing fast and accurate results with cited sources. It is ideal for use cases requiring quick access to reliable financial data, with results typically returned in 8-15 seconds through a single MCP endpoint.

Canonical page: https://skillsregistry.net/skills/drillr  
JSON: https://api.skillsregistry.net/v1/skills/drillr

## Description

Drillr gives AI agents access to comprehensive financial research data through a single MCP endpoint. It covers structured financials (income statements, balance sheets, 90+ tables), SEC filings with paragraph-level semantic search, market data across equities and crypto, earnings call transcripts, and alternative datasets including energy consumption and chip pricing. Results include cited sources, typically returned in 8–15 seconds.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/drillr)
- **Repository:** <https://github.com/little-grebe-inc/drillr-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "drillr"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/drillr` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/drillr/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt