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Archive Agent MCP Server

@shredEngineer

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基本情報

カテゴリ

AI とエージェント

ライセンス

GPL-3.0

トランスポート

stdio

作者

shredEngineer

Archive Agent MCP Server について

Find your files with natural language and ask questions.

#python#ocr#openai#rag#ollama#lm-studio#mcp-server

Archive Agent MCP Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

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Archive Agent MCP Server のツール

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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 Archive Agent?

Archive Agent is an intelligent file indexer that brings RAG (Retrieval Augmented Generation) to your command line. It indexes local documents (PDFs, images, Markdown, plaintext, and more) using automatic OCR, semantic chunking, and a local Qdrant vector database, then lets you search or query those files with natural language. It integrates with AI tools via a built-in MCP server — it is not a chatbot.

How to use Archive Agent?

First, install Docker and Python ≥3.10, then run git clone, cd Archive-Agent, chmod +x install.sh, ./install.sh. The script sets up a Python environment, installs dependencies, and deploys a Qdrant Docker container. After installation, configure an AI provider (OpenAI, OpenRouter, Ollama, or LM Studio) and run archive-agent to use the CLI (track, commit, search, query, GUI) or start the MCP server (archive-agent mcp).

Key features of Archive Agent

  • Semantic natural‑language search & query (RAG) on local files
  • Automatic OCR for images and PDFs (experimental)
  • Local indexing with self‑hosted Qdrant vector database
  • Supports OpenAI, OpenRouter (400+ models), Ollama, and LM Studio
  • Built‑in MCP server for workflow integration
  • Fully resumable parallel processing with AI cache & retry logic
  • Smart semantic chunking with context headers and reranking

Use cases of Archive Agent

  • Search a personal document archive using natural‑language questions
  • Query technical manuals, PDFs, or scanned images without manual browsing
  • Integrate document Q&A into an AI assistant or IDE via MCP
  • Index and search offline documents using local LLMs (Ollama/LM Studio)
  • Automate OCR and entity extraction from scanned images on a schedule

よくある質問

1

Is Archive Agent a chatbot?

No. Archive Agent is a file indexer and RAG engine that provides answers through a CLI, GUI, or MCP interface — it does not offer a conversational chatbot interface.

2

Which AI providers are supported?

OpenAI (or any OpenAI‑compatible API), OpenRouter (access to 400+ models), Ollama, and LM Studio. Local providers (Ollama/LM Studio) offer best privacy; remote APIs often give higher performance.

3

Can I change the AI provider after creating a profile?

No. The embeddings generated by one provider are incompatible with another. To switch providers, you must create a new profile.

4

Does Archive Agent require an internet connection?

Not for core indexing and querying if you use a local LLM (Ollama/LM Studio) and the local Qdrant database. However, installation and initial setup (e.g., downloading models) typically require internet.

5

What file types are processed?

Archive Agent natively ingests PDFs, images (with automatic OCR), Markdown, plaintext, and several other formats. Files are selected for tracking using pattern‑based inclusion/exclusion rules.

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