Lacuna Research MCP server

<!-- mcp-name: io.github.tiptreesystems/lacuna-research-mcp -->

Lacuna Research MCP

🔬 Ground your coding agent in novel ideas, papers, and the ML landscape

Lacuna Research MCP gives AI researchers' coding agents:

• Novel research proposals. Explore novel research ideas generated with Alien Science.
• Research directions. Navigate concept clusters with linked papers, authors, and proposals.
• Agent-ready literature. Search recent papers in markdown with source links.
• Researcher intelligence. Trace authors, publications, directions, impact, and related researchers.
• Landscape mapping. Compare venues, institutions, leading researchers, and publication activity.

Lacuna, built by Tiptree Systems, is a research map of machine learning: a heterogeneous knowledge graph linking papers, research directions, authors, venues, institutions, and generated research proposals, with a source trail from every derived object back to the exact paper and page that produced it. Its pipeline reconciles scholarly records from OpenAlex, OpenReview, DBLP, and arXiv; extracts concept elements from paper text and clusters them into research directions (Lacuna paper); and samples novel research proposals from those directions with Alien Science. The map spans more than 730,000 papers, 190,000+ author profiles, 38,000+ research directions, and 3,000+ research proposals built from over 15 million concept elements — and it grows continuously as new arXiv and other AI papers are ingested.

Install · First use · Tools · API reference · Configuration

Install

The easiest way to install Lacuna Research MCP is to ask your coding agent, such as Codex or Claude Code:

Install and configure the lacuna-research-mcp package from PyPI for this client.

For manual setup, the instructions below use uvx to run the latest tagged release from PyPI. Install uv first; Lacuna Research MCP requires Python 3.11 or newer.

Codex

Add the server with the Codex CLI:

codex mcp add lacuna-research -- uvx lacuna-research-mcp

Alternatively, add the following to ~/.codex/config.toml (or to .codex/config.toml in a trusted project for project-only setup):

[mcp_servers.lacuna-research]
command = "uvx"
args = ["lacuna-research-mcp"]

Run codex mcp list to verify the server is configured. The Codex app, CLI, and IDE extension share this configuration on the same machine.

Claude Code

Add the server for all of your projects with the Claude Code CLI:

claude mcp add --scope user lacuna-research -- uvx lacuna-research-mcp

Omit --scope user to add it only to the current project. Alternatively, add the following under the top-level mcpServers object in ~/.claude.json:

Shortened. The full README is on GitHub.