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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 The Alien Space of 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 The Alien Space of Science. The map spans more than 2.29 million papers, 215,000+ author profiles, 28,000+ research directions, 25,000+ research proposals, and 5,300+ venues — and it grows continuously as new arXiv and other AI papers are ingested.

Install · First use · Tools · API reference · Configuration

Install

Hosted MCP server (Claude connector)

Use Lacuna's hosted MCP server with any client that supports Streamable HTTP. No local installation is required.

https://lacuna.tiptreesystems.com/api/mcp

In Claude, open Customize → Connectors → + Add → Add custom connector. Name it Lacuna Research, paste the URL above, and select No sign in if prompted for authentication. Finish adding it, then enable it from + → Connectors in your conversation.

For Team and Enterprise workspaces, the connector must first be added under Organization settings → Connectors. See Claude's custom connector setup for details.

Local installation

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:

{
  "mcpServers": {
    "lacuna-research": {
      "type": "stdio",
      "command": "uvx",
      "args": ["lacuna-research-mcp"]
    }
  }
}

Run claude mcp get lacuna-research to verify the server is configured.

Claude Desktop

Open Settings → Developer → Edit Config, then add the server under mcpServers in claude_desktop_config.json:

{
  "mcpServers": {
    "lacuna-research": {
      "command": "uvx",
      "args": ["lacuna-research-mcp"]
    }
  }
}

Restart Claude Desktop after saving the file.

Other MCP clients

For any client that supports local stdio MCP servers, use this standard configuration:

{
  "mcpServers": {
    "lacuna-research": {
      "command": "uvx",
      "args": ["lacuna-research-mcp"]
    }
  }
}

Standalone command

Install the MCP server as a persistent command:

uv tool install lacuna-research-mcp
lacuna-research-mcp

Run it without installing a persistent command:

uvx lacuna-research-mcp

If this exits with a prerelease error (for example, "Python 3.14.0rc2 is a prerelease..."), your uv is using an early Python 3.14 prerelease that the MCP SDK does not support. Update uv (uv self update), install a released Python (uv python install 3.14), or run uvx --python 3.13 lacuna-research-mcp.

Self-hosted HTTP server

To serve remote MCP clients over Streamable HTTP instead of stdio:

uvx lacuna-research-mcp --transport streamable-http --host 0.0.0.0 --port 8000

The endpoint is /mcp. The server is stateless and answers with JSON, so it can run behind a load balancer without session affinity. With the default --host 127.0.0.1, the server accepts only localhost Host headers, so bind a non-loopback address when a reverse proxy forwards a public hostname.

Latest development version

PyPI contains tagged releases. To try the latest code from the main branch instead:

uvx --from git+https://github.com/tiptreesystems/lacuna-research-mcp.git lacuna-research-mcp

Local development

With uv:

git clone https://github.com/tiptreesystems/lacuna-research-mcp.git
cd lacuna-research-mcp
uv sync --extra dev
uv run lacuna-research-mcp

With pip:

cd <path-to-lacuna-research-mcp>
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -U pip
python -m pip install -e .

First use

After connecting the server, call:

1. search_lacuna(query="LLM jailbreak defense", search_type="hypothesis", limit=10)
2. search_lacuna(query="methods for detecting prompt injection attacks", search_type="paper", limit=10) (production lexical+semantic paper ranking by default)
3. get_hypothesis(hypothesis_id_or_url="bd35de182c2325ae")
4. get_paper(artifact_id_or_url="art_79c57fbfec094f26b79c422cf08fed34") (defaults to view="context")
5. get_direction(cluster_id_or_url=25108) (defaults to view="context")
6. search_lacuna(query="ImageNet", search_type="resource", resource_kind="dataset") (datasets linked to papers; follow up with get_resource)

Scope

The corpus covers machine learning and AI research: papers, research directions, authors' research output, venues, institutions, generated research hypotheses, and research resources (GitHub repositories, Hugging Face datasets and models, Zenodo records) linked to papers. It does not contain biographies, news, or non-research web content. Agents should answer questions outside that scope from other sources.

What it exposes

• search_lacuna Uses Lacuna's public /api/v1/search endpoint for directions, papers, authors, venues, institutions, hypotheses, and resources. Explicit paper searches (search_type="paper") use the server's production lexical+semantic ranker when the other ranking arguments remain at their defaults. Pass search_type="hypothesis" for hypothesis search. Pass search_type="resource" for code repositories, datasets, models, and demos linked to papers, optionally filtered with resource_kind (codebase, dataset, model, demo) and provider (github, huggingface, zenodo); for example, resource_kind="dataset" finds benchmark datasets. Resource search rejects date_from/date_to, venue, year sorts, and semantic ranking (resources carry no dates, venues, or embeddings).
• get_hypothesis(hypothesis_id_or_url, view="context") Hypothesis/proposal. view="context" (default) is a compact single-fetch proposal context (summary, abstract, linked directions); view="full" returns the server's version record with version history and signal counts. Proposal bodies are in versions[].markdown.
• get_direction(cluster_id_or_url, view="context") Research direction/cluster. view="context" (default) requests the compact agent-oriented summary; view="full" returns the raw cluster record.
• get_direction_papers(cluster_id_or_url, page, limit, view="compact") Paginated papers attached to a direction. view="compact" (default) returns citation-ready rows (id, url, title, year, venue, a few authors, abstract snippet); view="full" returns the raw upstream paper records.
• get_paper(artifact_id_or_url, view="context", figure_limit=None, include_resources=True) Paper lookup with available versions; use a version’s artifact ID to read it. Linked resources (code repositories, datasets, models, and demos) are included by default in context and full views; pass include_resources=False to omit them. Other views ignore this option. view="context" (default) requests the compact agent-oriented context; other views are "full", "preview", "blog", "figures", "concepts", or "neighbors". In context view, figure_limit caps the figure preview (server default 3; pass 0 to suppress previews while keeping a figures_truncated signal).
• get_resource(resource_id_or_url) Resource lookup by id (from resource search or get_paper's resources list) or Lacuna /resource/... URL: external URL, summary, facets (tasks, modalities, size, license), provider metrics, README/card excerpt, linked papers under publications (with paper_id and relationship such as dataset_for), related directions, and mentioned resources.
• Author tools: get_author_context(…, view="context"), get_author_papers, get_author_directions, and get_author_neighbors. Start with get_author_context, which defaults to the compact agent-oriented view (capped papers plus a readable impact_directions list instead of raw impact_clusters telemetry). Use the dedicated papers, directions, and neighbors tools to page through those collections without repeating the author context. view="full" returns the server-bounded full-shape context (collections remain capped at 100). Pass include_neighbors=true to explicitly include similar authors; this may add significant server latency.
• Venue and institution tools: get_venue_context(…, view="context"), get_institution_context(…, view="context"), get_institution_authors. Context tools default to compact (capped lists, duplicated blocks dropped; venue keeps a recent-activity slice that always includes the requested year). Use get_institution_authors to page through an institution's complete author list.

Wrapped APIs

| MCP tool | Lacuna API endpoint | | --- | --- | | `search_lacuna(query, search_type, limit, offset, author_id_or_url, date_f