agentmods.dev

mcp: Instructions file for Claude Code

CLAUDE.md

mcp CLAUDE.md is an instructions file for Claude Code from supadata-ai/mcp. It costs 1,574 tokens per session, scanned A, original, MIT.

Project instructions for an MCP server, a program that lets AI tools call Supadata services for web scraping and video transcripts.

In plain words
What is it for?
Use it when building, testing, linting, formatting, or starting this TypeScript server.
Why use it?
It gives coding agents the project context, standard commands, and ways to run focused tests without searching through the repository.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions Claude Code.

This is supadata-ai/mcp's own configuration. It tells Claude Code how to work on mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything mcp configures →

not rated 62repo 2mo ago A scan 1,574 tokens original MIT
View source ↗ supadata-ai/mcp supadata.ai
Reuse

Borrowing it

Nothing to install: this file belongs to supadata-ai/mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/supadata-ai/mcp/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/supadata-ai/mcp

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mcp CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/supadata-ai/mcp/claude-md.svg)](https://agentmods.dev/instructions/supadata-ai/mcp/claude-md)
Your own site
<a href="https://agentmods.dev/instructions/supadata-ai/mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/supadata-ai/mcp/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,574 This file is loaded in full into every session.
When invoked 1,574 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01574 $0.01574
Opus 5 $0.00787 $0.00787
Sonnet 5 $0.00315 $0.00315
Haiku 4.5 $0.00157 $0.00157

Measured 7d ago against content hash 946773b00a92, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 147 lines

How it starts

The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

This is a Model Context Protocol (MCP) server implementation for Supadata web scraping and video transcript integration. The project provides nine main tools: supadata_transcript, supadata_check_transcript_status, supadata_scrape, supadata_map, supadata_crawl, supadata_check_crawl_status, supadata_metadata, supadata_extract, and supadata_check_extract_status for video transcription, web scraping, URL discovery, batch crawling, media metadata retrieval, and AI-powered structured data extraction.

Key Commands

Development Commands

  • npm run build - Compile TypeScript to JavaScript and make executable
  • npm run test - Run Jest tests with ESM support
  • npm run lint - Run ESLint on TypeScript files
  • npm run lint:fix - Run ESLint with auto-fix
  • npm run format - Format code with Prettier
  • npm run start - Start the compiled server

Single Test Execution

  • npm run test -- --testNamePattern="should handle scrape request" - Run specific test
  • npm run test -- src/index.test.ts - Run specific test file

Architecture

MCP Server Structure

The server is built using the @modelcontextprotocol/sdk and runs on stdio transport. The main server logic is in src/index.ts with the following key components:

  • Server Creation: createServer() function creates an McpServer instance
  • Tool Registration: Nine tools are registered with input validation using Zod schemas
  • Error Handling: Comprehensive error handling with retry logic and exponential backoff
  • Configuration: Environment-based configuration with defaults

API Integration

The server integrates with Supadata's JavaScript SDK (@supadata/js) and provides:

  • Video Transcription: Extract transcripts from YouTube, TikTok, Instagram, Twitter, and file URLs
  • Web Scraping: Single page content extraction to Markdown
  • URL Mapping: Website URL discovery and indexing
  • Crawling: Asynchronous batch crawling of multiple pages
  • Media Metadata: Retrieve metadata from YouTube, TikTok, Instagram, and Twitter URLs
  • Structured Extraction: AI-powered extraction of structured data from video content
  • Status Checking: Monitor crawl, transcript, and extract job progress and retrieve results

Read the full file on GitHub · 147 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 147 lines · 1,574 tokens per session scan A 946773b00a92

Subscribe to this mod's changes

mcp CLAUDE.md is an instructions file published in the GitHub repository supadata-ai/mcp (62 stars, last pushed 2mo ago), licensed MIT. It adds 1,574 tokens to every session, about $0.0079 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

LLMaicrawlermcpscrapetiktok
Related

Other instructions, from other repositories

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens