Paper Memory Lite

Local-first MCP-style research memory for papers, notes, figures, experiment logs, and GitHub README files.

License: MIT Python SQLite FTS

_{Image source: public Semantic Scholar homepage screenshot, https://www.semanticscholar.org/. Used as a visual reference for paper search and research-memory workflows; not an endorsement by Semantic Scholar.}

Paper reading gets messy fast: one PDF has the key idea, one Markdown note has your interpretation, one experiment log has the actual failure, and one README has the code status. This project gives agents a tiny local memory layer that indexes those files and exposes search through a simple MCP-compatible stdio server.

It is intentionally small: no cloud database, no embeddings service, no account, no background daemon. Everything lives in a local SQLite file.

If this helps your research workflow, a star helps other people find it.

Features

• Index Markdown, text, JSON, YAML, and lightweight PDF text when optional PDF tooling is installed.
• Store paper notes, figure captions, experiment logs, repo READMEs, and daily briefings in one SQLite FTS database.
• Search snippets with source path, title, kind, and timestamp.
• Expose MCP-style tools:
  • index_research_folder
  • search_research_memory
  • get_daily_context
  • link_paper_to_experiment
  • summarize_evidence_pack
• Run as a CLI for smoke tests or as a stdio JSON-RPC server for agents.

Quick Start

git clone https://github.com/StaryMoon/paper-memory-mcp-lite.git
cd paper-memory-mcp-lite
python3 -m venv .venv
source .venv/bin/activate
pip install -e .

paper-memory index examples/sample_research
paper-memory search "continual deraining"
paper-memory daily

MCP Server

Add this to an MCP client configuration and adjust the path:

{
  "mcpServers": {
    "paper-memory-lite": {
      "command": "python3",
      "args": ["-m", "paper_memory_mcp_lite.server", "serve"],
      "env": {
        "PAPER_MEMORY_DB": "/absolute/path/to/paper-memory.sqlite"
      }
    }
  }
}

See docs/mcp-config.json for a copyable example.

Tool Behavior

Tool	Purpose
index_research_folder	Index a folder of Markdown, text, JSON, YAML, and optional PDF text.
search_research_memory	Search local research notes and return snippets with file paths.
get_daily_context	Retrieve the most recent notes, logs, and briefings for daily planning.
link_paper_to_experiment	Store a lightweight relationship between a paper note and an experiment log.
summarize_evidence_pack	Build an evidence pack from search results without pretending it is a full literature review.

CLI Examples

paper-memory index ~/Downloads/文稿/papers
paper-memory search "reasoning RL benchmark" --limit 8
paper-memory link papers/deepseek-r1.md experiments/grpo-ablation.md --note "baseline for reasoning radar"
paper-memory evidence "image restoration continual prompt"

Privacy Model

• Local SQLite database only.
• No telemetry.
• No API keys.
• No automatic background crawl.
• The indexer only reads folders you explicitly pass to it.

Related Projects

• ai-researcher-skills
• codegraph-memory-mcp-lite
• obsidian-research-brief-kit
• awesome-ai-paper-reproduction-radar

License

MIT.