Model Context Protocol server for arXiv PDF retrieval and LLM context generation.
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"paperstack-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# paperstack (Model Context Protocol) [](https://pypi.org/project/paperstack-mcp/) [](https://pypi.org/project/paperstack-mcp/) [](https://pypi.org/project/paperstack-mcp/) ## Overview `paperstack` is a production-grade Model Context Protocol (MCP) server focused on arXiv research retrieval. It provides: - arXiv Atom API search by ID/query - PDF download, validation, and cache - PDF text extraction (title, abstract, body, references) - Token-aware context chunking for LLM pipelines - CLI, API, and autonomous agent integration support --- ## Table of Contents 1. [Quickstart](#quickstart) 2. [Installation](#installation) 3. [Usage](#usage) 4. [MCP Server](#mcp-server) 5. [Project structure](#project-structure) 6. [Configuration](#configuration) 7. [Testing](#testing) 8. [Troubleshooting](#troubleshooting) 9. [Contributing](#contributing) 10. [License](#license) --- ## Quickstart ### 1. Clone repository ```bash git clone https://github.com/Aldrin-Joan/paperstack.git cd paperstack ``` ### 2. Set up Python environment (recommended) ```bash python -m venv .venv # macOS/Linux source .venv/bin/activate # Windows .venv\Scripts\activate ``` ### 3. Install dependencies ```bash pip install -r requirements.txt ``` ### 4. Run smoke test ```bash python test_smoke.py ``` --- ## Installation From source: ```bash pip install -e . ``` From PyPI: ```bash pip install paperstack-mcp ``` --- ## Usage ### CLI ```bash paperstack --help ``` Run server locally: ```bash python -m src.mcp_server ``` ### Python API ```python from paperstack_mcp import entrypoint # import alias for the package from src.arxiv_client import ArxivClient from src.pdf_fetcher import PdfFetcher from s…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.