IlyaGusev Academia MCP vs Infranodus MCP Server Infranodus

A side-by-side look at the IlyaGusev Academia MCP and Infranodus MCP Server Infranodus MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

IlyaGusev Academia MCP logoIlyaGusev Academia MCPResearchSearch arXiv and ACL Anthology, retrieve citations and references, and browse web sources to accel…48FairAuth: no auth requiredInfranodus MCP Server Infranodus logoInfranodus MCP Server InfranodusResearch · Local subprocess (stdio)Map text into knowledge graphs to create a structured representation of conceptual relations and t…69GreatAuth: api key required

Verdict: choose IlyaGusev Academia MCP for research work; choose Infranodus MCP Server Infranodus for research as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

IlyaGusev Academia MCP logoChoose IlyaGusev Academia MCP when

  • You need dedicated capabilities in the Research domain.
  • Its auth model fits you: No auth required.
  • You have the keys it needs: WORKSPACE_DIR, OPENROUTER_API_KEY, EXA_API_KEY, BRAVE_API_KEY, TAVILY_API_KEY, PORT, ENABLE_AUTH, TOKENS_FILE.
  • You want tools like arxiv_search, arxiv_download, anthology_search.
Explore IlyaGusev Academia MCP

Infranodus MCP Server Infranodus logoChoose Infranodus MCP Server Infranodus when

  • You need dedicated capabilities in the Research domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: API key required.
  • You want tools like generate_knowledge_graph, create_knowledge_graph, generate_ontology_graph.
Explore Infranodus MCP Server Infranodus

Feature & specification comparison

Rows where the two servers differ are marked.

SpecIlyaGusev Academia MCP logoIlyaGusev Academia MCPInfranodus MCP Server Infranodus logoInfranodus MCP Server Infranodus
CategoryResearchResearch
Quality signal48/100 · Fair69/100 · Great
Install commandNot confirmed yetConfirmed
Transport—Local subprocess (stdio)
AuthNo auth requiredAPI key required
PricingFreeNot declared
Required env varsWORKSPACE_DIROPENROUTER_API_KEYEXA_API_KEYBRAVE_API_KEYTAVILY_API_KEYPORTENABLE_AUTHTOKENS_FILENone listed
Verified ownerCommunity listingCommunity listing
GitHub stars93104
Directory activity 3 views 0 installs 0 upvotes 5 views 0 installs 0 upvotes
Tools1140

Tools & capabilities

IlyaGusev Academia MCP tools 11

  • arxiv_searchQuery arXiv with field-specific queries and filters.
  • arxiv_downloadFetch a paper by ID and convert to structured text (HTML/PDF modes).
  • anthology_searchSearch ACL Anthology with fielded queries and optional date filtering.
  • hf_datasets_searchFind Hugging Face datasets with filters and sorting.
  • s2_get_citationsList papers citing a given arXiv paper (Semantic Scholar Graph).
  • s2_get_referencesList papers referenced by a given arXiv paper.
  • visit_webpageFetch and normalize a web page.
  • web_searchUnified search wrapper; available when at least one of Exa/Brave/Tavily keys is set.
  • compile_latexCompile LaTeX to PDF in `WORKSPACE_DIR`.
  • read_pdfExtract text per page from a PDF.
  • document_qaAnswer questions over provided document chunks (requires LLM).

Infranodus MCP Server Infranodus tools 40

  • generate_knowledge_graphGenerate a knowledge graph with main topics, topical clusters, concepts, concepts (nodes) relations (edges) and structural gaps. Only use when explicitly asked to analyze a text or generate a knowledge graph. Do not use for short clarifying questions that you already have an answer to from the context of the conversation.
  • create_knowledge_graphCreate a knowledge graph in InfraNodus from text or from a URL, save it, and provide its name and a link to it for future use.
  • generate_ontology_graphUse AI to generate a reasoning ontology knowledge graph (entities and the relations between them) and optionally save it as a InfraNodus graph. Three sources, provide exactly one: prompt (a topic — one AI call), text (a long document or a structural digest of a project, chunked server-side), or sourceGraphName (an existing graph — e.g. a fully ingested repo, vault, or corpus — whose statements are read back, chunked, and condensed into an ontology). Set ontologyMode: 'codebase' for software projects, or 'procedural' to write a DIGEST of how the project works (prose statements with [[wikilinks]], not relation triples) from an already-uploaded graph — save it as <repo|vault>-<project>-digest for optimize_knowledge_base. Use to get a rich overview, a reasoning map of a topic, or a condensed 'how it fits together' graph of a large corpus.
  • memory_add_relationsAdd relations to the InfraNodus memory from text, save it, and provide its name and a link to it for future use.
  • memory_get_relationsProvide a list of relations from the InfraNodus memory for a given concept or entity
  • analyze_existing_graph_by_nameExtract and analyze the content of an existing InfraNodus graph from your account.
  • analyze_textExtract and analyze a graph from text, URL, YouTube video transcript, or an existing InfraNodus graph.
  • generate_content_gapsGenerate content gaps from text, URL, or an existing graph using knowledge graph analysis.
  • generate_topical_clustersGenerate topics and clusters of keywords from text, URL, or an existing graph using knowledge graph analysis.
  • generate_research_questionsAnalyze text or an existing graph and generate innovative research questions based on the content gaps identified between the topical clusters. Provide either text, url, or graphName. Can be used to improve the text and the discourse it relates to
  • generate_research_ideasAnalyze text or an existing graph and generate innovative research ideas based on the content gaps identified between the topical clusters inside the text that can be used to improve the text and the discourse it relates to.
  • generate_responses_from_graphUse text, URL, or an existing InfraNodus knowledge graph and generate responses and expert advice based on a prompt provided.
  • +28 more on the listing page

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.

IlyaGusev Academia MCP

No confirmed install command for IlyaGusev Academia MCP yet — follow the setup steps linked from its listing page rather than a guessed package name.

Infranodus MCP Server Infranodus

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "infranodus-mcp-server-infranodus": {
      "command": "npx",
      "args": [
        "-y",
        "infranodus-mcp-server"
      ]
    }
  }
}

Frequently asked questions

IlyaGusev Academia MCP is categorized under Research and uses an install path we have not confirmed yet. Infranodus MCP Server Infranodus belongs to Research and uses a local stdio subprocess. Pick IlyaGusev Academia MCP for research work and Infranodus MCP Server Infranodus 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. IlyaGusev Academia MCP has no confirmed install command yet — follow its own setup instructions.

IlyaGusev Academia MCP is listed as free. Auth: no auth required. Infranodus MCP Server Infranodus has no declared pricing — check the project's own site. Auth: api key required. 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 ilyagusev-academia-mcp and infranodus-mcp-server-infranodus as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, IlyaGusev Academia MCP has a quality signal of 48/100 (Fair) with 3 views, 0 installs and 93 GitHub stars. Infranodus MCP Server Infranodus has 69/100 (Great) with 5 views, 0 installs and 104 GitHub stars.