Lacuna Research MCP vs Paperswithcode
A side-by-side look at the Lacuna Research MCP and Paperswithcode MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Lacuna Research MCP for research work as a local process; choose Paperswithcode for research as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Lacuna Research MCP when
- You need dedicated capabilities in the Research domain.
- You prefer a local stdio subprocess transport.
- You want tools like
search_lacuna, get_hypothesis, get_direction.
Choose Paperswithcode when
- You need dedicated capabilities in the Research domain.
- You prefer a local stdio subprocess transport.
- You want tools like
search_papers, trending_papers, get_paper.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Research | Research |
| Quality signal | 60/100 · Good | 53/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 7 | 0 |
| Directory activity | 1 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | 13 | 4 |
| Full listing | View Lacuna Research MCP | View Paperswithcode |
Tools & capabilities
Lacuna Research MCP tools 13
search_lacunaSearch Lacuna's ML/AI corpus for papers, research directions, authors, venues, institutions, novel research hypotheses, and research resources (code repositories, datasets, models, and demos linked to papers). For novel ML/AI research ideas, use search_type="hypothesis", then get_hypothesis on promising results. search_type accepts all, cluster, paper, author, institution, venue, hypothesis, or resource. Use paper for literature and get_paper to read a result. Use other sources for biographies, news, and non-research web content. Resources: search_type="resource" searches GitHub repositories, Hugging Face datasets/models, and Zenodo records that Lacuna has linked to at least one paper. To find benchmark or evaluation datasets, use search_type="resource" with resource_kind="dataset" (for example query "image classification benchmark" or a dataset name like "ImageNet"). resource_kind accepts codebase, dataset, model, or demo (one value or a list); provider accepts github, huggingface, or zenodo. Both filters require search_type "resource" or "all" (with either filter set, only resources are returned). Each result has an external `url`, a Lacuna `context_url`, and `linked_paper_count`; call get_resource on its id to list the linked papers (with their relationship to the resource), then get_paper on those papers for reported results and numbers. Resource search does not support date_from/date_to, venue, year sorting, or semantic ranking. ranking_profile accepts: - default / lexical (default): production ranking; relevance-sorted paper searches combine lexical and semantic retrieval when fields is unset. - semantic: conceptual paper retrieval; supported for paper and all. - bm25_title_abstract / bm25: lexical paper matching over those fields. sort accepts relevance (default), year_desc, or year_asc. Semantic ranking cannot use year sorting; constrain recency with date_from/date_to instead. date_from and date_to are inclusive YYYY, YYYY-MM, or YYYY-MM-DD bounds. author_id_or_url constrains a paper search to one author. Pass an author ID or Lacuna author page URL; it requires search_type="paper". fields optionally restricts and weights lexical fields, for example "title^4,abstract". Supported names are title, abstract, summary, concepts, name, top_names, and venue, plus description, topics, provider_key, and paper_titles for resources (a resource's title already includes its description, topics, README text, and linked paper titles). Fields must exist on the selected search_type, weights must be within 0 < weight <= 100, and fields cannot be combined with semantic ranking.get_hypothesisFetch a generated novel ML/AI research proposal from Lacuna. Use after search_lacuna(search_type="hypothesis") to inspect a proposal. view selects the response shape: - "context" (default, recommended): compact single-fetch proposal context — summary_markdown, abstract, and linked directions, with the raw upstream record (whose markdown duplicates summary_markdown) dropped server-side. - "full": the server's version record, including version history and signal counts. Proposal bodies are in versions[].markdown. Use only when you need versions or signals.get_directionFetch a Lacuna research direction/cluster. Use a numeric cluster ID (for example 25005) or a direction URL ending in that number. view selects the response shape (`context` typically contains the fields `full` provides plus the agent-oriented summary content): - "context" (default, recommended): compact agent-oriented summary with summary_markdown, capped papers/authors/related_directions, and truncation markers. - "full": raw upstream cluster record only. Cheaper than context when you only need basic cluster metadata.get_direction_papersFetch paginated papers associated with a Lacuna research direction/cluster. view selects the per-paper shape: - "compact" (default, recommended): citation-ready rows (id, url, title, year, venue, a few authors, abstract snippet). Drops the raw upstream info blob and levels.cluster internals that otherwise dominate the payload. - "full": the complete upstream paper records. Much larger; use only when you need the raw metadata (openalex/dblp/arxiv ids, etc.).get_paperFetch a Lacuna paper by artifact id or paper URL. include_resources adds linked resources (code repositories, datasets, models, and demos) in context and full views by default. Pass False to omit them; other views ignore this option. Pass a resource entry's id to get_resource for further details. view selects the response shape. `context` requests Lacuna's compact agent-oriented context by default, while the four single-field views (blog/figures/concepts/neighbors) return isolated sub-resources: - "context" (default, recommended): agent-oriented summary with summary_markdown, authors, and a small figure preview. Start here for almost everything. Available versions are included when present; to read another version, use its artifact ID from the returned version list. - "full": raw upstream paper record. Cheaper than context when you only need basic metadata. - "preview": compact card with unique fields `excerpt`, `excerpt_kind`, `bookmarked`. Use for citation-style display. - "blog": just the summary_markdown content, without the rest of the context envelope. - "figures": just the figures list. - "concepts": just the concepts list. - "neighbors": just the related-papers list. figure_limit (context view only) caps the figure preview (server default 3). Pass 0 to suppress figure previews while keeping a `figures_truncated` signal.get_resourceFetch a Lacuna research resource (code repository, dataset, model, or demo). Accepts a resource artifact ID (art_...) or a Lacuna resource URL containing that ID (/resource/<slug>/art_...). The response includes the external url, a summary, facets (tasks, modalities, size, license, access), provider metrics, a README/card excerpt, `publications` (linked papers with paper_id, title, venue, year, and relationship such as dataset_for or code_for), related research directions, and other resources mentioned by this one. Pass a publication's paper_id to get_paper to read the paper and its reported results.get_author_papersFetch one page of an author's papers, ordered from newest to oldest.get_author_directionsFetch one page of an author's named research directions.get_author_contextFetch agent-oriented context for a Lacuna author. Author profiles describe research output (papers, directions, impact). A free-text `affiliation` field may be present but can be incomplete or outdated and may not represent current employment; the corpus has no biography or employment history, so do not infer those from this data. view selects the response shape: - "context" (default, recommended): Lacuna's compact author context — capped readable papers and an `impact_directions` list (named research directions) in place of the raw numeric `impact_clusters` telemetry, with the duplicated nested author record dropped server-side. - "full": the bounded full-shape author context (raw `impact_clusters`, nested author record; server collections are capped at 100). Set include_neighbors=True to include similar authors as named, linkable records. Neighbor computation may add significant server latency.get_author_neighborsFetch one ranked page of neighboring/similar Lacuna authors.get_venue_contextFetch agent-oriented context for a Lacuna venue, optionally scoped to a year. Venue keys are opaque hashes (e.g. "d7bf22905bd6"), never human-readable names like "icml". Find the key first via search_lacuna(search_type="venue") or pass a /venue/... page URL. view selects the response shape: - "context" (default, recommended): compact venue context — capped top authors, non-placeholder top clusters, and a recent-activity slice (the requested `year` is always included), with the duplicated venue block and full year histogram dropped server-side. - "full": the complete venue context (full year histogram, all top authors/ clusters, duplicated venue record).get_institution_contextFetch agent-oriented context for a Lacuna institution. view selects the response shape: - "context" (default, recommended): compact institution context — capped top authors with the duplicated institution block dropped server-side. - "full": the complete institution context shape (duplicated institution record and a bounded author list with explicit truncation metadata). Use get_institution_authors to page through the complete author list.- +1 more on the listing page
Paperswithcode tools 4
search_papersSearch machine-learning / AI research papers (via Hugging Face Papers, the successor to Papers with Code). Returns arXiv id, title, authors, community upvotes, and a linked GitHub repo when available. Use for "papers on <topic>", "recent ML research about X".trending_papersToday's trending ML/AI papers (or a given day's), ranked by community upvotes, via Hugging Face Papers. Use for "what are the hot AI papers", "trending ML research", "top papers this week".get_paperGet full detail for a paper by its arXiv id (e.g. "2312.00752"): title, authors, abstract, AI-generated summary and keywords, community upvotes, and counts of linked models / datasets / demo Spaces.get_repositoriesFind IMPLEMENTATIONS of a paper (by arXiv id): the linked GitHub repository plus the most popular Hugging Face models, demo Spaces, and datasets that implement or reproduce it — the "papers with code" view. Use for "code/implementation for <paper>", "models trained on <paper>".
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Lacuna Research MCP
{
"mcpServers": {
"lacuna-research-mcp": {
"command": "uvx",
"args": [
"lacuna-research-mcp"
]
}
}
}
Paperswithcode
{
"mcpServers": {
"paperswithcode": {
"command": "npx",
"args": [
"-y",
"@pipeworx/mcp-paperswithcode"
]
}
}
}
Frequently asked questions
Lacuna Research MCP is categorized under Research and uses a local stdio subprocess. Paperswithcode belongs to Research and uses a local stdio subprocess. Pick Lacuna Research MCP for research work and Paperswithcode for research.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Lacuna Research MCP has no declared pricing — check the project's own site. Paperswithcode has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add lacuna-research-mcp and paperswithcode as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Lacuna Research MCP has a quality signal of 60/100 (Good) with 1 views, 0 installs and 7 GitHub stars. Paperswithcode has 53/100 (Good) with 0 views, 0 installs and 0 GitHub stars.