mcpField
U
Universal Source Management System

Universal Source Management System

Local
github.com/YUZongminDatabases19Updated 33w ago

About Universal Source Management System

Universal Source Management System is a lightweight FastMCP server for managing literature, notes, entity links and reading lists in a local SQLite database. It suits researchers who organize papers, books and webpages, and it stores identifiers in a normalized form.

Key features

  1. 01Local SQLite-backed source management
  2. 02Notes attached to sources
  3. 03Entity links between sources and concepts
  4. 04Read-only database inspection tools
  5. 05Resources for identifier lookup and reading lists
  6. 06Batch source import with duplicate detection

Use cases

  1. 01Organizing a literature list of papers and books
  2. 02Looking up sources by DOI or arXiv identifier
  3. 03Recording how sources relate to named concepts

MCP support

This project is an MCP server that exposes source management tools and source://, reading-list:// and entity:// resources to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"sqlite-literature-management-fastmcp": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"build"
]
}
}
}
Run commanddocker run -i --rm build

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocibuild

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Universal Source Management System

A lightweight FastMCP server for managing literature, notes, entity links, and reading-list resources in a local SQLite database.

Current Scope

This repository provides:

  • Local SQLite-backed source management
  • Notes attached to sources
  • Entity links between sources and named concepts
  • Read-only database inspection tools
  • MCP resources for source lookup and reading lists
  • Normalized identifier storage with a transitional JSON cache

It does not integrate with MCP Memory Server or an external memory graph.

Quick Start

  1. Create a database from the current schema:
sqlite3 sources.db < create_sources_db.sql
  1. Install the FastMCP server with your database path:
fastmcp install sqlite-paper-fastmcp-server.py --name "Source Manager" -e SQLITE_DB_PATH=/path/to/sources.db
  1. Optional: use the checked-in demo fixture at examples/sources.db.

Docker

This server can be packaged as a containerized stdio MCP server.

Build the image:

docker build -t sqlite-lit-mcp .

Run it with a persistent SQLite volume:

mkdir -p data
docker run --rm -i \
  -e SQLITE_DB_PATH=/data/sources.db \
  -v "$(pwd)/data:/data" \
  sqlite-lit-mcp

Notes:

  • The image defaults SQLITE_DB_PATH to /data/sources.db.
  • If the database file does not exist, the container initializes it from create_sources_db.sql.
  • If you are mounting an older database, apply the required migrations under migrations/ before starting the server.
  • This repo runs as a stdio MCP server, so there is no HTTP port to expose by default.

With Docker Compose:

docker compose run --rm sqlite-lit-mcp

Current Tool Surface

Implemented tools:

  • read_query
  • list_tables
  • describe_table
  • get_table_stats
  • get_database_info
  • vacuum_database
  • add_sources
  • add_notes
  • update_status
  • add_identifiers
  • link_to_entities
  • get_source_entities
  • update_entity_links
  • remove_entity_links
  • get_entity_sources

Implemented resources:

  • source://<id>
  • source://by-identifier/<type>/<value>
  • reading-list://unread
  • reading-list://reading
  • entity://<entity_name>

Schema Notes

The current schema centers on four tables:

  • sources
  • source_identifiers
  • source_notes
  • source_entity_links

sources.identifiers is still kept as a transitional JSON cache, but identifier lookups now use source_identifiers.

Supported identifier types:

  • semantic_scholar
  • doi
  • arxiv
  • openalex
  • pmid
  • isbn
  • url

Supported entity relation types:

  • discusses
  • introduces
  • extends
  • evaluates
  • applies
  • critiques
  • supports
  • contradicts
  • refutes

Lightweight provenance fields live on sources:

  • provider
  • discovered_via
  • discovered_at

The schema now uses PRAGMA user_version = 3.

Migration

If you have a version 0 or version 1 database, apply:

sqlite3 /path/to/sources.db < migrations/2026-03-09__normalize-identifiers.sql
sqlite3 /path/to/sources.db < migrations/2026-03-09__expand-entity-relation-types.sql

If you already migrated to version 2, apply:

sqlite3 /path/to/sources.db < migrations/2026-03-09__expand-entity-relation-types.sql

These migrations:

  • adds source_identifiers
  • backfills identifier rows from the legacy JSON column
  • adds provenance fields
  • expands source_entity_links.relation_type to include supports, contradicts, and refutes
  • updates PRAGMA user_version to 3

The server checks PRAGMA user_version on connection and will reject older databases until they are migrated.

Package Layout

The implementation is organized under sqlite_lit_server/:

  • app.py creates the FastMCP instance and registers tools/resources
  • db.py owns connection setup and schema-version checks
  • repository.py keeps SQL-heavy lookup logic close to the data layer
  • tools_admin.py, tools_sources.py, and tools_entities.py hold the MCP tools
  • resources.py defines the MCP resources

sqlite-paper-fastmcp-server.py remains as a thin compatibility shim.

Batch Import Sources

add_sources is the batch import entrypoint for new sources. It accepts one argument named sources, where each item is:

[title, source_type, identifier_type, identifier_value, initial_note]

initial_note must be either null or an object with both title and content.

Supported source_type values:

  • paper
  • webpage
  • book
  • video
  • blog

Supported identifier_type values:

  • semantic_scholar
  • doi
  • arxiv
  • openalex
  • pmid
  • isbn
  • url

Duplicate handling:

  • Exact identifier matches return Source already exists together with the existing source payload.
  • Title-based fuzzy matches return Potential duplicates found. Please verify or use add_identifiers if these are the same source.
  • Successful batch writes return one result per input item in the same order as the request.

Example MCP/JSON payload:

{
  "sources": [
    [
      "Attention Is All You Need",
      "paper",
      "arxiv",
      "1706.03762",
      {
        "title": "Initial thoughts",
        "content": "Transformers start here."
      }
    ],
    [
      "OpenAlex Import",
      "paper",
      "openalex",
      "W1234567890",
      null
    ]
  ]
}

Example Python call:

add_sources([
    (
        "Attention Is All You Need",
        "paper",
        "arxiv",
        "1706.03762",
        {
            "title": "Initial thoughts",
            "content": "Transformers start here.",
        },
    ),
    (
        "OpenAlex Import",
        "paper",
        "openalex",
        "W1234567890",
        None,
    ),
])

The same tool payloads work whether you start the server locally or through Docker with docker compose run --rm sqlite-lit-mcp.

Batch Write Conventions

Plural write tools accept lists and return a per-input result list in the same order. Related batch tools include:

  • add_notes
  • add_identifiers
  • update_status
  • link_to_entities

Example Usage

Add another identifier:

add_identifiers([
    (
        "Attention Is All You Need",
        "paper",
        "arxiv",
        "1706.03762",
        "semantic_scholar",
        "204e3073870fae3d05bcbc2f6a8e263d9b72e776",
    ),
])

Read a source resource:

source://by-identifier/arxiv/1706.03762

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.