HasData Google Scholar vs Infranodus MCP Server Infranodus
A side-by-side look at the HasData Google Scholar 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.
Verdict: choose HasData Google Scholar for research work as a local process; 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?
Choose HasData Google Scholar when
- You need dedicated capabilities in the Research domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
HASDATA_API_KEY. - You want tools like
hasdata_google_scholar_case_law_getScholarCaseLawOpinion, hasdata_google_scholar_cite_getScholarCitationFormats, hasdata_google_scholar_scholar_getScholarSearchResults.
Choose 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.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Research | Research |
| Quality signal | 63/100 · Good | 69/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | API key required |
| Pricing | Not declared | Not declared |
| Required env vars | HASDATA_API_KEY | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 11 | 104 |
| Directory activity | 1 views 0 installs 0 upvotes | 5 views 0 installs 0 upvotes |
| Tools | 3 | 40 |
| Full listing | View HasData Google Scholar | View Infranodus MCP Server Infranodus |
Tools & capabilities
HasData Google Scholar tools 3
hasdata_google_scholar_case_law_getScholarCaseLawOpinionGet Scholar Case Law Opinion Looks up a Google Scholar Case Law opinion by its `caseId` (as returned in a google/scholar organic result's `caseId`, when searching with `asSdt` set to a case-law court scope, or in another case-law result's `citedCases`). Returns the case title, party names, court, procedural history, argued/decided dates, short citations, docket numbers, and every case cited within the opinion (grouped by cited case with a ready-to-call `hasdataLink`). Use to build legal-research and case-law-analysis workflows, or to walk a citation graph one cited case at a time.hasdata_google_scholar_cite_getScholarCitationFormatsGet Scholar Citation Formats Looks up citation formats and export links for a single Google Scholar organic search result, identified by its `resultId` (as returned in a google/scholar organic result). Returns formatted citation snippets (MLA, APA, Chicago, Harvard, Vancouver) and reference-manager export links (BibTeX, EndNote, RefMan, RefWorks). Use to build citation/bibliography features or complete a research workflow started with google/scholar.hasdata_google_scholar_scholar_getScholarSearchResultsGet Scholar Search Results Scrapes Google Scholar for a query with author:/source: search helpers, year range (asYlo/asYhi), cited-by and all-versions lookups (cites/cluster), review-article and citation-inclusion filters, language/language-restrict, start/num pagination, and asSdt to scope to case law (asSdt=2006 for all courts, 2003 for Federal courts only, or 4/6/3 plus comma-separated court codes for specific courts) or toggle patents. Returns each organic result with title, link, snippet, publication info (authors with profile links), cited-by count and link, related-articles link, and all-versions count and link; a case-law result links to a scholar_case?case= page and carries a ready-to-call caseHasdataLink. Use for academic research, literature review automation, citation tracking, grounding research agents with scholarly sources, and walking case law straight into google/scholar-case-law.
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 entityanalyze_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 togenerate_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.
HasData Google Scholar
{
"mcpServers": {
"hasdata-google-scholar": {
"command": "npx",
"args": [
"-y",
"@hasdata/google-scholar-mcp"
],
"env": {
"HASDATA_API_KEY": "YOUR_HASDATA_API_KEY_HERE"
}
}
}
}
Infranodus MCP Server Infranodus
{
"mcpServers": {
"infranodus-mcp-server-infranodus": {
"command": "npx",
"args": [
"-y",
"infranodus-mcp-server"
]
}
}
}
Frequently asked questions
HasData Google Scholar is categorized under Research and uses a local stdio subprocess. Infranodus MCP Server Infranodus belongs to Research and uses a local stdio subprocess. Pick HasData Google Scholar 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.
HasData Google Scholar has no declared pricing — check the project's own site. 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 hasdata-google-scholar and infranodus-mcp-server-infranodus as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, HasData Google Scholar has a quality signal of 63/100 (Good) with 1 views, 0 installs and 11 GitHub stars. Infranodus MCP Server Infranodus has 69/100 (Great) with 5 views, 0 installs and 104 GitHub stars.