Everyrow MCP Server

@futuresearch

リポジトリ

基本情報

カテゴリ

その他

トランスポート

stdio

作者

futuresearch

投稿者

Callum McMahon

Everyrow MCP Server について

概要はまだありません

Everyrow MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "everyrow": {
      "command": "uvx",
      "args": [
        "everyrow-mcp"
      ],
      "env": {
        "EVERYROW_API_KEY": "${EVERYROW_API_KEY}"
      }
    }
  }
}

Everyrow MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is Everyrow?

Everyrow is an SDK to run LLM research agents at scale on pandas dataframes, enabling intelligent sorting, filtering, merging, deduplication, and column addition. It scales to tens of thousands of LLM calls or web research agents from a single Python method.

How to use Everyrow?

Install via pip install everyrow, get an API key at everyrow.io/api-key, then use Python with pandas and Pydantic models to run operations like screen, rank, or research. Integrate with Claude Code, Gemini CLI, Codex CLI, or Cursor via plugins.

Key features of Everyrow

Screen rows by criteria that need judgment (10k rows)
Rank and score rows from research (10k rows)
Deduplicate where fuzzy matching fails (20k rows)
Merge tables when keys don't match (5k rows)
Web research agents on every row (10k rows)
Async operations with crash recovery via fetch_task_data

Use cases of Everyrow

Filter job listings for remote-friendly senior roles with salary disclosure
Deduplicate messy CRM exports where exact matching fails
Merge two tables without clean join keys
Research company funding rounds and lead investors at scale
Classify and label thousands of dataframe rows using LLM judgment

よくある質問

What Python version is required?

Python 3.12 or newer is required to install and run Everyrow.

How do I get an API key?

Go to everyrow.io/api-key to obtain an API key; you receive $20 in free credit.

Can Everyrow perform web research?

Yes, use `single_agent` for one row or `agent_map` for parallel web research agents on every row, tuned for deep research and cost efficiency.

What if my script crashes during an async operation?

Print the task ID after submitting, then use `fetch_task_data` with that ID to recover the results later.

Which coding agent plugins are supported?

Plugins are available for Claude Code, Gemini CLI, Codex CLI, and Cursor, each with installation steps in the README.

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