# sec-edgar

> Use this tool when you need to access and analyze financial data from the US Securities and Exchange Commission (SEC) EDGAR database, solving problems related to financial research and compliance. It provides an interface to retrieve and process EDGAR filings, taking company names or CIK numbers as input and outputting relevant financial data. Utilize sec-edgar in contexts where financial data analysis, research, or compliance is required, such as investment decisions or regulatory reporting.

Canonical page: https://skillsregistry.net/skills/punitarani-sec-edgar  
JSON: https://api.skillsregistry.net/v1/skills/punitarani-sec-edgar

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/punitarani/sec-edgar)

## 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": "punitarani-sec-edgar"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/punitarani-sec-edgar` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/punitarani-sec-edgar/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