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Literature Memory Server Fastmcp MCP

TBD

Unclaimed last commit a year ago devtools
34Low

Scored 7 months ago · breakdown

About Literature Memory Server Fastmcp MCP

Literature Memory Server Fastmcp MCP is an MCP server published by zongmin-yu in the Developer Tools category: tBD.

The repository has 3 stars and 1 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/zongmin-yu/literature-memory-server-fastmcp-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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  • ✓README presentThe repository ships documentation.

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README

IN PROGRESS

A flexible system for managing various types of sources (papers, books, webpages, etc.) and integrating them with knowledge graphs.

Features

Core Features

  • Universal source identification with internal UUID system
  • Support for multiple source types (papers, webpages, books, videos, blogs)
  • Multiple identifier support per source (arxiv, DOI, semantic scholar, ISBN, URL)
  • Structured note-taking with titles and content
  • Status tracking (unread, reading, completed, archived)

Entity Integration

  • Link sources to knowledge graph entities
  • Track relationships between sources and entities
  • Flexible relation types (discusses, introduces, extends, etc.)
  • Integration with memory graph

Prerequisites

This system integrates with the MCP Memory Server for persistent knowledge graph storage.

Quick Start

  1. Create a new SQLite database with our schema:
# Create a new database
sqlite3 sources.db < create_sources_db.sql
  1. Install the source management server:
# Install for Claude Desktop with your database path
fastmcp install source-manager-server.py --name "Source Manager" -e SQLITE_DB_PATH=/path/to/sources.db

Schema

Core Tables

-- Sources table
CREATE TABLE sources (
    id UUID PRIMARY KEY,
    title TEXT NOT NULL,
    type TEXT CHECK(type IN ('paper', 'webpage', 'book', 'video', 'blog')) NOT NULL,
    identifiers JSONB NOT NULL,
    status TEXT CHECK(status IN ('unread', 'reading', 'completed', 'archived')) DEFAULT 'unread'
);

-- Source notes
CREATE TABLE source_notes (
    source_id UUID REFERENCES sources(id),
    note_title TEXT NOT NULL,
    content TEXT NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (source_id, note_title)
);

-- Entity links
CREATE TABLE source_entity_links (
    source_id UUID REFERENCES sources(id),
    entity_name TEXT,
    relation_type TEXT CHECK(relation_type IN ('discusses', 'introduces', 'extends', 'evaluates', 'applies', 'critiques')),
    notes TEXT,
    PRIMARY KEY (source_id, entity_name)
);

Usage Examples

1. Managing Sources

Add a paper with multiple identifiers:

add_source(
    title="Attention Is All You Need",
    type="paper",
    identifier_type="arxiv",
    identifier_value="1706.03762",
    initial_note={
        "title": "Initial thoughts",
        "content": "Groundbreaking paper introducing transformers..."
    }
)

# Add another identifier to the same paper
add_identifier(
    title="Attention Is All You Need",
    type="paper",
    current_identifier_type="arxiv",
    current_identifier_value="1706.03762",
    new_identifier_type="semantic_scholar",
    new_identifier_value="204e3073870fae3d05bcbc2f6a8e263d9b72e776"
)

Add a webpage:

add_source(
    title="Understanding Transformers",
    type="webpage",
    identifier_type="url",
    identifier_value="https://example.com/transformers",
)

2. Note Taking

Add notes to a source:

add_note(
    title="Attention Is All You Need",
    type="paper",
    identifier_type="arxiv",
    identifier_value="1706.03762",
    note_title="Implementation details",
    note_content="The paper describes the architecture..."
)

3. Entity Linking

Link source to entities:

link_to_entity(
    title="Attention Is All You Need",
    type="paper",
    identifier_type="arxiv",
    identifier_value="1706.03762",
    entity_name="transformer",
    relation_type="introduces",
    notes="First paper to introduce the transformer architecture"
)

Query sources by entity:

get_entity_sources(
    entity_name="transformer",
    type_filter="paper",
    relation_filter="discusses"
)

Best Practices

  1. Source Management

    • Use consistent titles across references
    • Provide as many identifiers as available
    • Keep notes structured with clear titles
    • Use appropriate source types
  2. Entity Linking

    • Be specific with relation types
    • Add contextual notes to relationships
    • Verify entity names against memory graph
    • Keep entity relationships focused

Technical Details

  1. Source Identification

    • Internal UUID system for consistent referencing
    • Multiple external identifiers per source
    • Flexible identifier types (arxiv, doi, url, etc.)
    • Title and type based fuzzy matching
  2. Data Organization

    • Structured notes with titles
    • Clear source type categorization
    • Entity relationship tracking
    • Status management

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Add tests for new features
  4. Submit a pull request

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Literature Memory Server Fastmcp MCP

How do I install Literature Memory Server Fastmcp MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Literature Memory Server Fastmcp MCP safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Literature Memory Server Fastmcp MCP still maintained?

The last commit was a year ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.