"Character Name and Profile Generator" matching MCP servers:

Enables users to create, validate, view, and export system stock-and-flow maps from a versioned JSON model through MCP-capable hosts over local stdio or hosted Streamable HTTP. Supports causal-loop and nested-level mapping while keeping submitted model content with the caller and requiring no LLM provider key.

Enables Codex to control a Gephi 3D network view through natural language, including network generation, 3D layout, node focus and neighbor highlighting, layered views, and PNG/PDF export.

Generates formal string diagram visualizations of Lushy brick compositions, enabling zero-cost diagram generation and recursive self-documentation based on category theory.

Generates professional PDF reports with live Power BI dashboards, charts, and insights from plain-text prompts containing CSV data.

Generates column charts and statistic infographics as PNG images with SVG source links, letting users request finished charts conversationally and receive inline image results.

Options analytics an agent can drive: import a permitted chain, solve implied volatility, build a sixteen-Greek ladder, map dealer gamma walls, rank twenty-three structures, run a GARCH-t simulation with a convergence gate, and backtest with modelled premiums. Twelve stdio tools; every output is a schema-validated JSON file with source, assumptions and a degraded flag. Research only, no orders.

A unified Model Context Protocol server for data engineering and analytics that lets LLM clients query, profile, transform, and visualize data using DuckDB and PySpark, while keeping raw data out of the model's context through read-only, bounded, and audited operations.

Provides live weather radar and text-based radar maps for any location via the get_weather tool, returning structured data and character grid visualizations readable by both humans and LLM agents.

Enables MCP-capable agents to profile datasets and render CSV/TSV/TXT/JSON data into standalone interactive ECharts HTML charts fully offline, returning the HTML artifact plus rendering statistics in the same response.

Enables AI assistants to query Oracle AI Database read-only, profile tables, and render result sets as PNG charts.

Exposes ASCIIFlow drawing primitives as tools to enable AI assistants to generate ASCII wireframes and diagrams from natural language descriptions. It provides commands for creating canvases and drawing boxes, lines, arrows, and text using a character-grid coordinate system.

PBIForge — Power BI .pbix generator MCP server generate .pbix files from dashboard image and prompts using a local hosted llm

Enables coding agents to turn finished sessions into Strava-style achievement cards with distance, elevation, effort, badges, and personal records, plus profile, activity feed, season recap, and leaderboard tools—all measured from session transcripts rather than self-reported.

Lets coding agents load toolsets by name to drive a local browser-based viewer for ROS 2 robots, including displaying lidar/map data and plotting odometry, through a token-protected local connection without writing to the robot.

Provides an MCP interface for publication-quality chemical structure and reaction rendering from SMILES/InChI/molblock, with validation and name parsing. Enables AI agents to draw molecules and reactions as images.

A hosted remote MCP server that connects marketing platforms such as Google Ads, GA4, Search Console, Meta Ads, Microsoft Ads, LinkedIn Ads, TikTok Ads, and Google Business Profile, enabling plain-English performance analysis, KPI and budget tracking, report creation, and previewed account changes.

Enables AI assistants and editors to profile, clean, and analyze messy CSV/Excel files directly through MCP tools such as profile_dataset, clean_dataset, and list_sheets.

A stateless MCP server that generates interactive report widgets and survey builder UIs, using MCP Apps for rich visualizations and long-polling for live updates.

MCP server that turns coding agents into data analysts: attach CSV/Parquet/JSON/XLSX or databases, profile data, run read-only SQL, and render Vega-Lite charts as SVG files.

Enables creating interactive tier lists in MCP-compatible chats, ranking options into tiers via drag-and-drop or chat, undoing changes, and exporting results as PNG images.

Enables an AI assistant to connect to and control Rigol DHO900-series oscilloscopes over VISA, configure acquisition, trigger, channels and timebase, use the built-in waveform generator, capture screenshots, measurements and waveform data, and assemble and export test reports as DOCX or HTML.

Enables querying global and regional DEM datasets for point and batch elevations, neighbourhood elevation and slope statistics, charts, composite terrain maps, and 3D perspective surfaces through a local bridge to the hosted Geospatial System location-profile MCP server.

Enables AI assistants to render interactive charts as generative UI inline in chat, including bars, lines, areas, donuts, tooltips, table views, and built-in series analysis.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables querying your spreadsheet using natural language questions; provides read-only tools for schema, sample data, and structured query execution with auditable computation traces.

Enables an AI assistant to query a user's RQrun training data through read-only tools for activities, period statistics, training load and status, run-level predictions, intensity distribution, calendars, and profile details, and to render pace/heart-rate and weekly mileage charts as PNGs.

Enables personal finance management through natural language: log expenses, snap receipt photos, and import bank statements. Computes budgets, trends, and net worth in any currency, with data persisted and accessible via MCP.

Enables deterministic multi-timeframe XAUUSD market analysis and TradingView chart automation through MCP, allowing AI assistants to read charts, manage Pine Scripts, and execute analysis workflows with profile-gated access.

Acts as a bridge between AI assistants and StarRocks databases, enabling direct SQL execution, database and table exploration, schema/data overviews, and metric access without complex client-side setup. It also generates Plotly charts from query results and caches overviews in memory for faster repeated requests.

Enables an AI agent to generate and reconfigure real-time banking interfaces by exposing MCP tools that return UI schemas and personalized financial components based on customer context and situation. It supports dynamic situation detection, security rules, and demo profiles for adaptive dashboards.

Enables AI assistants to execute SQL, explore databases and tables, retrieve schemas and data overviews, access system metrics, and generate Plotly charts directly from StarRocks databases.

Generates matplotlib charts via a FastAPI service, supporting line, bar, scatter, and pie charts with customizable labels and data.

Enables AI assistants to execute SQL against StarRocks, explore databases and tables, retrieve schemas and detailed overviews, and generate Plotly charts from query results.

Provides tools to inspect dataset schema, profile, preview, and execute read-only SQL queries on uploaded CSV/Excel files.

Enables AI assistants to query and explore StarRocks databases, inspect schemas, metrics, and sample data, and generate Plotly charts from query results without complex client-side setup.

Enables AI clients to discover datasets and author dashboards in Dashboard Builder through natural language, while preserving per-user permissions and audit trails via a secure API-key gated gateway.

Acts as a bridge between AI assistants and StarRocks databases, enabling direct SQL query and DDL/DML execution, database and table exploration, schema and system-metric retrieval, and cached table or database overviews. It also supports generating Plotly charts directly from query results.

Acts as a bridge between AI assistants and StarRocks databases, enabling direct SQL execution, listing databases and tables, retrieving table schemas and system metrics, generating data overviews with sample rows, and rendering query results as Plotly charts — all without complex client-side setup.

Enables querying and managing Redash data sources, queries, dashboards, alerts, and users through the Model Context Protocol.

Bridges AI assistants with StarRocks databases so they can run SQL queries and DDL/DML commands, explore databases, tables and schemas, and inspect system metrics. It also generates Plotly charts from query results and provides cached table and database overviews with column definitions, row counts and sample data.