BrunoSan ArXiv Intelligence

de.brunosanPublished by brunosan.deOfficial publisherv1.0.0Updated Oct 24, 2026

AI research intelligence for AI, ML, NLP, vision and robotics with citations and entity graphs.

VerifiedStreamable HTTPWeb executableWeb Search & ScrapingKnowledge & MemoryData & Analytics

Overview

AI-generated overview

Lets an assistant search a live arXiv AI/ML paper graph, inspect citations, entities, authors, institutions and linked code repositories.

What you can do
Provides 16 tools over a remote arXiv paper graph for cs.AI, ML, NLP, vision and robotics. The assistant can run full-text search with boolean and phrase operators, fetch a paper with its authors, references and linked GitHub repos, and rank entities, authors and institutions. It can also trace citation networks, find papers mentioning two entities together, follow research tracks over time, and check pipeline status.
When to use it
Useful for literature reviews, tracking how a benchmark, model or method rises or declines over time, finding influential papers by citation count, and mapping which labs and GitHub organizations produce research code.
Requirements
A remote endpoint reached over streamable HTTP; no packages, environment variables, headers or authentication are declared. Network access to the endpoint is required.
Before you install
The data is a live third-party paper graph, so coverage depends on its pipeline progress and backfill frontier, and citation counts only include papers with resolvable arXiv IDs in its database. No credentials are requested, and no write, send or delete actions are described.

Installation

In SourceWeft

  1. Open BrunoSan ArXiv Intelligence in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/de.brunosan%2Farxiv/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "brunosan-arxiv-intelligence": {
      "type": "http",
      "url": "https://arxiv.mcp.brunosan.de/mcp"
    }
  }
}

Tools

16

arxiv_search_papers

Full-text search over the live cs.AI/ML paper graph using FTS5. Searches title AND abstract. Supports boolean operators: AND, OR, NOT, phrase matching ("exact phrase"), prefix (term*). Args: query: FTS5 search query. E.g. 'LoRA fine-tuning', '"chain of thought"', 'RLHF NOT PPO' category: Filter by primary category. Options: cs.AI, cs.LG, cs.CL, cs.CV, cs.RO date_from: ISO date filter, e.g. '2024-01-01' date_to: ISO date filter, e.g. '2025-12-31' empirical_only: Only papers marked as empirical by LLM pass (if available) has_code_only: Only papers with code release (llm_has_code=1, if available) limit: Max results (default: 20, max: 50)

Parameterslimitqueryrequiredapi_keydate_tocategorydate_fromhas_code_onlyempirical_only

arxiv_get_paper

Full paper object with all connected data. Returns: paper metadata, author list with positions, matched entities, references (up to 100), and linked GitHub repos. Args: arxiv_id: ArXiv ID, e.g. '2402.01234' or '2402.01234v2'

Parametersapi_keyarxiv_idrequired

arxiv_top_entities

Entity ranking by mention count across all papers. title_only=True is a powerful relevance filter: a paper mentioning MMLU in the title IS about MMLU, not just using it as one of many benchmarks. Args: type: Filter by entity type: benchmark, model, method, dataset (optional, default: all) date_from: Only count mentions in papers published from this date date_to: Only count mentions in papers published until this date title_only: Only count mentions where entity appears in the paper title limit: Max results (default: 20, max: 50)

Parameterstypelimitapi_keydate_todate_fromtitle_only

arxiv_entity_trend

How often is an entity mentioned over time? Shows the rise (or fall) of a benchmark, model, method, or dataset across the research literature — per month, quarter, or year. Example: 'LoRA' — watch it explode in 2023-2024. Example: 'BERT' — watch it decline as LLMs dominate. Args: entity_name: Entity to track, e.g. 'LoRA', 'MMLU', 'RAG', 'GPT-4' granularity: Time grouping: month (default), quarter, year

Parametersapi_keyentity_namerequiredgranularity

arxiv_top_authors

Top researchers ranked by paper count, with role filter. role='last_author' is the PI filter — finds lab directors and group leaders who drive research agendas. In academic AI, the last author IS the boss. role='first_author' finds the PhD students and postdocs doing the work. role='any' counts all papers regardless of position. Args: role: Author position filter: any (default), first_author, last_author category: Filter by primary category: cs.AI, cs.LG, cs.CL, cs.CV, cs.RO date_from: ISO date filter, e.g. '2024-01-01' date_to: ISO date filter, e.g. '2025-12-31' limit: Max results (default: 20, max: 50)

Parametersrolelimitapi_keydate_tocategorydate_from

arxiv_author_papers

All papers by a researcher, with their position on each paper. Uses fuzzy name matching (LIKE) to handle name variations. Returns papers sorted newest first. Args: author_name: Researcher name, e.g. 'Yann LeCun', 'lecun' (partial match works) limit: Max results (default: 20, max: 50)

Parameterslimitapi_keyauthor_namerequired

arxiv_most_cited

Most cited papers — ranked by inbound citation count. This answers the question every researcher, VC, and journalist asks first: 'What are the most influential papers in AI right now?' Counts how many papers in our database cite each target paper. Only papers with resolvable ArXiv IDs in their references are counted. Args: category: Filter citing papers by category (optional) date_from: Only count citations from papers published from this date date_to: Only count citations from papers published until this date limit: Max results (default: 20, max: 50)

Parameterslimitapi_keydate_tocategorydate_from

arxiv_citation_network

Citation graph for a paper — who cites it, or what does it cite? direction='cited_by': Papers in our database that cite this paper. direction='citing': Papers that this paper cites (its references). depth=2: Expands one hop further (depth-2 neighbors). Hard cap: 200 total. Args: arxiv_id: ArXiv paper ID, e.g. '2402.01234' direction: 'cited_by' (inbound) or 'citing' (outbound, default: cited_by) depth: Graph depth: 1 or 2 (default: 1)

Parametersdepthapi_keyarxiv_idrequireddirection

arxiv_co_occurrence

Papers that mention BOTH entity A and entity B. Answers questions like: - 'Which papers use both GPT-4 and RLHF?' - 'Where do LoRA and MMLU appear together?' - 'Papers combining RAG and Chain-of-Thought?' The intersection reveals research that explicitly bridges two concepts. Args: entity_a: First entity name, e.g. 'GPT-4', 'LoRA', 'MMLU' entity_b: Second entity name, e.g. 'RLHF', 'Chain-of-Thought' date_from: ISO date filter date_to: ISO date filter limit: Max results (default: 20, max: 50)

Parameterslimitapi_keydate_toentity_arequiredentity_brequireddate_from

arxiv_institution_ranking

Institution ranking by paper count. Primary signal: author_affiliations extracted from ArXiv HTML. Secondary signal (include_github_orgs=True): adds GitHub org counts as a complementary signal. Many papers have no affiliation in HTML but do have a GitHub org link — combining both gives a fuller picture. Note: affiliation data is extracted from HTML and may be incomplete (fetch completion is reported live by arxiv_pipeline_status; extraction quality is a separate signal). Args: date_from: ISO date filter date_to: ISO date filter include_github_orgs: Also show GitHub org ranking as second signal limit: Max results (default: 20, max: 50)

Parameterslimitapi_keydate_todate_frominclude_github_orgs

arxiv_repo_landscape

GitHub repository landscape — which orgs and repos produce research code? Shows the open-source output of the research community. 'openai', 'google-deepmind', 'microsoft', 'huggingface' etc. ranked by how many papers link to their repos. org_filter='huggingface' shows all HuggingFace repos with papers. Args: org_filter: Filter to a specific GitHub org, e.g. 'openai', 'google-deepmind' date_from: Only papers published from this date date_to: Only papers published until this date limit: Max results per ranking (default: 20, max: 50)

Parameterslimitapi_keydate_todate_fromorg_filter

arxiv_tracks

List stable ArXiv research-track objects with definitions and live counts.

Parametersapi_key

arxiv_track_papers

Chronological papers inside one stable research track. Args: track: Track slug or exact name, e.g. 'ai-agents' or 'multi-agent-systems'. date_from: Optional ISO date lower bound. date_to: Optional ISO date upper bound. has_code_only: Restrict to papers with confirmed code signal. limit: Max results (default 20, max 50).

Parameterslimittrackrequiredapi_keydate_todate_fromhas_code_only

arxiv_track_trend

Research volume for one stable track by month, quarter or year.

Parameterstrackrequiredapi_keygranularity

arxiv_pipeline_status

Full system status — database counts, pipeline progress, frontier, quality. Returns: - Paper/author/entity/ref/repo counts - Pipeline progress: html_fetched %, whitelist_matched %, llm_processed % - Frontier: how far back the backfill has reached - Quality report: last run timestamp and overall status - Quality log: last 5 quality check runs from quality_log table

Parametersapi_key

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

72% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts

    Publish an icon in the registry entry.

  • Documentation15 pts

    Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.

  • LicenseNot applicable

    A hosted service is used under its provider's terms, so no license is expected here. This check is left out of the percentage.

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