Legiscan MCP vs Infranodus MCP Server Infranodus

generate_knowledge_graph

Generate 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_graph

Create 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_graph

Use 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_relations

Add relations to the InfraNodus memory from text, save it, and provide its name and a link to it for future use.

memory_get_relations

Provide a list of relations from the InfraNodus memory for a given concept or entity

analyze_existing_graph_by_name

Extract and analyze the content of an existing InfraNodus graph from your account.

analyze_text

Extract and analyze a graph from text, URL, YouTube video transcript, or an existing InfraNodus graph.

generate_content_gaps

Generate content gaps from text, URL, or an existing graph using knowledge graph analysis.

generate_topical_clusters

Generate topics and clusters of keywords from text, URL, or an existing graph using knowledge graph analysis.

generate_research_questions

Analyze 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_ideas

Analyze 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_graph

Use text, URL, or an existing InfraNodus knowledge graph and generate responses and expert advice based on a prompt provided.