"Assistance with Generating Code for Graph Visualization" matching MCP servers:

Enables LLMs to perform OSINT link-analysis by exposing transforms (DNS, WHOIS, Shodan, etc.) as MCP tools for autonomous investigation and graph enrichment.

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

An MCP server for HF radio propagation analytics using the IONIS dataset collection, enabling natural language queries about band conditions, propagation paths, and solar correlations.

Enables searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

Enables deep research evidence synthesis and citation verification by generating structured research graphs through the Model Context Protocol.

A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.

A scientific reasoning framework that leverages graph structures and the Model Context Protocol (MCP) to process complex scientific queries through an Advanced Scientific Reasoning Graph-of-Thoughts (ASR-GoT) approach.

Enables searching for upcoming academic conferences and events from WikiCFP by keywords, returning detailed information including dates, locations, submission deadlines, and related resources.

MCP server for ARRL Logbook of The World (LoTW) that enables querying confirmations, uploaded QSOs, DXCC credits, and user activity through any MCP-compatible AI assistant. Part of the qso-graph project, it is read-only and requires LoTW credentials for authenticated tools.

An automated system that processes raw text through a three-stage pipeline to assess data quality, enhance information, and generate structured knowledge graphs. It provides tools for triple extraction with confidence scoring and creates interactive HTML visualizations of the resulting graph.

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Enables AI agents to analyze and link citations across multiple research sources, building cross-citation graphs and resolving consensus from conflicting findings. It exposes this capability as a deterministic, zero-dependency MCP server that plugs into Claude Desktop, Cursor, and other MCP-compliant clients.

Custom MCP server for NotebookLM that adds audio source upload, YouTube source ingestion, source readiness polling, and transcript export, complementing standard Q&A and audio overview tools.

Enables autonomous research workflows to construct and analyze multi-source cross-citation graphs and resolve consensus from structured outputs via MCP.

Institutional-grade quantitative stock analysis and research signals for AI agents via the Model Context Protocol (MCP).

Free competitive pricing intelligence for SMB CPG brands. Check where any product price sits in its Amazon category, track pricing trends, and compare products — no NielsenIQ or SPINS subscription needed.

Enables querying WSPR beacon data including live spots, band activity, top beacons, propagation paths, and SNR trends through any MCP-compatible AI assistant.

An MCP server that lets Large Language Models interact with Stata software to perform regression analysis and other statistical operations.