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memex

Memex for Model Context Protocol

Memex is a tool for Model Context Protocol (MCP) that allows you to analyze web content and add it to your knowledge base.

The tool was inspired by the Memex project by Vannevar Bush.

Requirements

You will need API keys for the following services:

The knowledge base produced by this tool is stored as Markdown files so they can be viewed with any Markdown viewer but Obsidian is recommended.

Related MCP server: Documentation Crawler & MCP Server

Installation

pip install mcp-memex

Add the following to your claude_desktop_config.json and replace the placeholders with the actual paths and API keys:

{
  "mcpServers": {
    "memex": {
      "command": "uv",
      "args": [
        "--directory",
        "PATH_TO_LOCAL_MEMEX_REPO",
        "run",
        "mcp-memex",
        "--index",
        "PATH_TO_MEMEX_INDEX",
        "--workspace",
        "PATH_TO_OBSIDIAN_VAULT"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "YOUR-API-KEY",
        "FIRECRAWL_API_KEY": "YOUR-API-KEY",
        "VOYAGE_API_KEY": "YOUR-API-KEY"
      }
    }
  }
}

Usage

Start by asking Claude a question with a list of URLs to reference.

What is the capital of France? "https://en.wikipedia.org/wiki/France"

Once Claude has finished analyzing the content, you will see the results in your Obsidian vault. You can then ask questions about the content and Memex will use the knowledge base to answer your questions.

What is the capital of France?

Development

To run the tool locally, you can use the following command:

npx @modelcontextprotocol/inspector \
  uv \
  --directory PATH_TO_LOCAL_MEMEX_REPO \
  run \
  mcp-memex \
  --index PATH_TO_MEMEX_INDEX \
  --workspace PATH_TO_OBSIDIAN_VAULT

Then open the inspector and connect to the server.

http://localhost:5173?timeout=30000

Available Tools

3 tools
analyze_web_contentA

Analyze multiple web pages and extract relevant information based on your query. This tool fetches and processes the content from provided URLs to answer your specific questions.

Inputs: query (required), urls (required).

save_artifactB

Save an artifact to the knowledge base

Inputs: content (required).

search_knowledge_baseB

Search through previously analyzed content in the knowledge base using natural language. This tool helps you find relevant information from your stored content.

Inputs: query (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.6/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool targets a distinct action: analyze web content, save to knowledge base, and search the knowledge base. There is no overlap in their purposes.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case (analyze_web_content, save_artifact, search_knowledge_base), making them predictable and easy to understand.

    Tool Count4/5

    With only 3 tools, the server feels slightly under-scoped for a knowledge base system, but it may be intentionally focused on core web analysis and storage/search functionality.

    Completeness3/5

    The tool set covers creating artifacts and searching, but lacks update, delete, or listing capabilities, which are notable gaps for managing a knowledge base over time.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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