# Stockfilm. Authentic Vintage Footage

> Stockfilm. Authentic Vintage Footage — stockfilm-stockfilm-mcp. Use this tool when you need to access authentic vintage footage for your projects, as it provides a vast library of 217,000+ genuine 8mm home movie clips from the 1930s-1980s. It solves problems related to finding unique, historical content and streamlines the licensing process through instant payments and rights verification. With text search, visual similarity, and rough-cut timeline builder tools, it offers a user-friendly interface for discovering and utilizing vintage footage.

Canonical page: https://skillsregistry.net/skills/stockfilm-stockfilm-mcp  
JSON: https://api.skillsregistry.net/v1/skills/stockfilm-stockfilm-mcp

## Description

Search and license 217,000+ authentic vintage 8mm home movie clips from the 1930s-1980s. Remote MCP server with 6 tools over Streamable HTTP. Text search, visual similarity, rough-cut timeline builder, rights verification, and instant licensing via x402 USDC payments on Solana and Base. Every frame is real archival film... no AI-generated content.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-24

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-08-24

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/stockfilm/stockfilm-mcp)

## 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": "stockfilm-stockfilm-mcp"
    }
  }
}
```

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