# About Lune Research

Lune connects AI agents with research knowledge and tools built for scientific
workflows. Add Lune to an AI app such as Claude, Codex, Cursor, or VS Code, then
ask a research question in plain English. The agent can search top-tier
conference papers, inspect abstracts and metadata, follow citation trails, read
full text when available, and consult curated guidance for the work around the
paper.

## Why we built it

AI can produce a plausible answer without checking whether the literature
supports it. That is not enough for a literature review, a novelty claim, an
evaluation plan, or a technical decision with real consequences. Lune retrieves
the research first. It gives the agent sources it can parse, compare, and cite,
so a reader can inspect where the answer came from.

## How Lune grounds an answer

A plain-English question becomes a search across the Lune corpus. Results
include paper titles, authors, venue and publication metadata, abstracts,
citation relationships, and stable source links. When full text is available,
the agent can retrieve the relevant sections and check the passages behind a
claim. When the corpus does not contain enough evidence, the answer should say
so instead of filling the gap from model memory.

## How the corpus works

Lune focuses on top-tier academic conferences selected with established CORE
and CCF rankings. It builds the corpus from published conference metadata,
open-access repositories, and citation records. Where lawful full text is
available, the ingestion pipeline parses and indexes it for retrieval. Lune
does not redistribute paywalled articles. Public paper pages expose rights-safe
metadata and abstracts, while authenticated tools apply the permissions and
usage rules attached to each credential.

## Guidance for scientific workflows

Finding papers is only part of research. Lune also maintains a curated guidance
library for literature reviews, evaluation design, ablation studies, peer
review, research writing, and venue selection. An agent can retrieve this
guidance alongside the literature, which helps researchers and technical teams
move faster from an early idea to a decision or draft that is ready for
scrutiny.

For high-stakes work, Lune keeps sources visible, separates evidence from
inference, and gives the agent research-specific tools instead of asking it to
improvise a scientific workflow.

## How to use Lune

The product is the toolset. Agents connect through the hosted
[Streamable HTTP MCP server](https://luneresearch.com/docs/mcp), an official connector or plugin, or
the published local MCP package. The [Lune command line app](https://luneresearch.com/docs/cli) can
configure local clients. The Assistant, Critique, and Workspace pages in the
dashboard are working examples of the same tools, not separate sources of
evidence.

## Who operates Lune

Lune is operated by Retrograde Labs, a research and software company. Product
support, privacy requests, and legal notices use separate published contact
channels so each request reaches the right owner. See the [contact page](https://luneresearch.com/contact)
for those addresses, the [Privacy Policy](https://luneresearch.com/legal/privacy) for data practices,
and the [developer index](https://luneresearch.com/developers) for connector, plugin, and MCP setup.