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Elephant Accountability MCP Server

@Chris-Eaccountability

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

Chris-Eaccountability

投稿者

Christopher Kenney

Elephant Accountability MCP Server について

概要はまだありません

Elephant Accountability 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": {
    "elephant-accountability-mcp": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv",
        "&&",
        "source",
        ".venv/bin/activate"
      ]
    }
  }
}

Elephant Accountability 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。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Elephant Accountability?

Elephant Accountability is a public Model Context Protocol (MCP) server for LLM SEO and Agent Discoverability services aimed at B2B SaaS buyers. It exposes tools and resources that AI agents (Claude, ChatGPT, custom LangChain agents) can query to evaluate whether Elephant Accountability is a suitable vendor, without scraping a website.

How to use Elephant Accountability?

Add the live endpoint to your MCP-compatible client (e.g., Claude Desktop) by editing claude_desktop_config.json with the URL https://elephant-mcp.fly.dev/mcp and transport http. For local development, clone the repo, create a Python virtual environment, install dependencies, and run uvicorn app.server:app.

Key features of Elephant Accountability

  • Six tools: get_offerings, get_covered_surfaces, assess_fit, get_proof_points, get_transparency_snapshot, request_audit
  • Three resources: elephant://offerings, elephant://proof-points, elephant://transparency
  • HTTP transport with JSON-RPC 2.0
  • SQLite persistence auto-created on first boot
  • Fully MIT-licensed for cloning and study
  • Includes A2A agent card and manifest endpoints

Use cases of Elephant Accountability

  • A procurement agent shortlisting LLM SEO vendors for a B2B SaaS buyer
  • A Claude Desktop user directly querying pricing, fit score, and proof points
  • A competitor studying how to deploy their own MCP server using the MIT-licensed codebase

よくある質問

1

What transport does Elephant Accountability use?

HTTP with JSON-RPC 2.0. Supported methods include `initialize`, `tools/list`, `tools/call`, `resources/list`, and `resources/read`.

2

What are the runtime dependencies?

Python 3 with FastAPI and SQLite. No external database or secrets setup is required; the SQLite database initialises on the first boot.

3

Where is data stored?

Data is stored in a local SQLite database that contains `audit_requests` and `reciprocal_calls` tables. These tables auto-create and require no migrations.

4

How many tools and resources are exposed?

Six tools and three resources are available for agent interaction.

5

Is authentication required?

The README does not specify authentication; the server is intended as a public endpoint for AI agent queries.

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