InfraNodus

InfraNodus MCP Server enables you to integrate InfraNodus knowledge graphs and network analysis into your AI workflows. It provides a dedicated MCP endpoint that lets you analyze text, generate knowledge graphs, discover content gaps, and augment responses in LLM chats and AI assistants.

How to use

You connect your MCP client to InfraNodus MCP Server to analyze text and generate knowledge graphs that enrich your AI conversations. Use the HTTP endpoint for remote access or run a local MCP server to configure your client with a local connection. Once connected, call the provided tools through your MCP client to analyze text, generate graphs, detect gaps, and extract structured insights that improve prompt quality and answer accuracy.

How to install

Prerequisites: have Node.js 18+ installed on your system. If you plan to run locally, also ensure you have access to an InfraNodus API key.

# Quick remote setup using the InfraNodus MCP Server URL
# No local installation needed if you use the remote server
# Your MCP client should point to the remote URL:
https://mcp.infranodus.com

Two common setup paths are available: use the remote MCP server via HTTP/SSE, or run a local MCP server using the NPCs shown in examples. The remote URL approach is the simplest to start, while local setup gives you full control over the server and API key handling.

# 1) Remote MCP server access (no local server needed)
# Use the provided URL in your MCP client configuration
# You will authenticate via OAuth in your client when connecting

To run a local server via NPX, start the server with the following command structure and supply your API key when prompted.

npx -y infranodus-mcp-server

If you need to explicitly set the API key in your local configuration, provide it as an environment variable when starting the local MCP server.

Additional sections

Configuration helps you connect your MCP client to InfraNodus in the way that suits your workflow. The server supports both a remote HTTP endpoint and local stdio configurations that expose the MCP tools to your client.

Security and API keys: you decide whether to use the remote server or a local server with your own InfraNodus API key. If you run locally, protect your API key and ensure it is not exposed in client configurations.

Common usage patterns include analyzing a document to extract topics and clusters, generating a knowledge graph from text, and identifying content gaps to guide research or content development.

Troubleshooting tips: ensure the MCP client configuration points to a valid server URL or a valid local command, verify the API key when required, and restart your client after making changes.

Available tools

generate_knowledge_graph

Convert text into a knowledge graph by extracting topics, concepts, and relationships and identifying clusters and patterns.

analyze_existing_graph_by_name

Retrieve and analyze an existing graph from your InfraNodus account and export full statistics.

analyze_text

Analyze a text, URL, or YouTube transcript and extract a graph with topics, clusters, statements, and an AI summary.

generate_content_gaps

Detect missing connections in discourse, identify underexplored topics, generate research questions, and suggest content development opportunities.

generate_topical_clusters

Generate topics and clusters from text using knowledge graph analysis to establish topical authority.

generate_contextual_hint

Provide a high-level topical overview to augment prompts and improve prompt quality in LLM workflows.

generate_research_questions

Create research questions bridging content gaps from text, URL, or an existing graph to drive prompts.

generate_research_ideas

Generate innovative ideas based on content gaps to improve the discourse.

optimize_text_structure

Analyze bias and coherence, balance discourse, and deepen analysis by addressing content gaps.

generate_responses_from_graph

Produce responses derived from an existing InfraNodus graph for integration into AI workflows.

develop_conceptual_bridges

Identify latent ideas that connect the text to broader discourse and discover hidden themes.

develop_latent_topics

Extract underdeveloped topics and provide actionable development suggestions.

develop_text_tool

Comprehensive analysis that combines content gaps, latent topics, and bridges in sequence.

create_knowledge_graph

Create a knowledge graph in InfraNodus from text and provide a link.

overlap_between_texts

Create graphs from multiple texts and find overlaps in topics and keywords.

merged_graph_from_texts

Build a merged graph from multiple texts/URLs to reveal clusters and gaps.

difference_between_texts

Compare graphs to identify what is missing from one text relative to others.

analyze_google_search_results

Generate a graph of keywords and topics from Google search results to understand current supply.

analyze_related_search_queries

Graph the search queries suggested by Google to understand demand.

search_queries_vs_search_results

Graph keyword combinations that are searched but not yet present in results.

generate_seo_report

Evaluate content for SEO by comparing with search results and queries to identify gaps.

memory_add_relations

Add relations to InfraNodus memory from text and save to a specified graph.

memory_get_relations

Retrieve relations from InfraNodus memory for specific entities or contexts.

retrieve_from_knowledge_base

Query a knowledge base with natural language and retrieve related statements.

search

Search through existing InfraNodus graphs and public graphs.

fetch

Fetch a specific search result for a graph.