"Historical cryptocurrency market data" matching MCP servers:

Blueprint is an MCP server that enables AI assistants to create C4 software architecture diagrams from structured data.

Enables AI assistants to interact with Autodesk Civil 3D, allowing them to retrieve project data, create/modify/delete drawing elements, and execute code to automate Civil 3D operations.

Local-first MCP server for storing and managing project architecture, modules, data flow, and usage examples with complete privacy.

MCP server for viewing software architecture diagrams and data.

Enables developers and product owners to scan a codebase and extract a readable business overview—features, roles, access control, data model, and endpoints—along with findings on missing or inconsistent rules, and generate shareable HTML or Markdown reports and diagrams.

Enables AI assistants to interact with Autodesk Revit to query project data, manage elements, and execute generated code via the Model Context Protocol. It provides full compatibility with GitHub Copilot and Claude to automate BIM modeling workflows.

Enables agents to turn short specs, Mermaid, or CSV data into laid-out SVG diagrams and charts, and to validate and audit the result for overlapping labels, arrows through boxes, and spilling text before showing it to anyone. Exposes render, describe, validate, audit, export, and infer tools so drawings can be generated, checked, and converted to formats like PNG, PDF, draw.io, and Excalidraw.

Connects AI coding agents to Circuitry's visual workflow platform, enabling them to create and sync code nodes from project files, understand user-drawn flowcharts and diagrams, generate visual flowcharts, and create data visualizations like spreadsheets and charts.

Enables Claude to draw architectural plans, 3D models, and BIM data in FreeCAD through natural language.

Analyzes runtime data objects to suggest optimal UI component instructions for a low-code renderer using structural heuristics. It automatically maps data patterns to specific UI elements like tables, carousels, and cards to streamline interface generation.

Connects AI models to MasterGo design tools, enabling retrieval of DSL data, component documentation, and metadata from MasterGo design files for structured component development workflows.

Enables AI agents to query architecture context, data contracts, and blast radius to prevent cross-repo architectural breakage before merging.

Integrates Archaic's AI-powered architecture analysis with Claude Code, enabling interactive exploration of component connections, data flows, and system structure through natural language.

Enables read-only access to Sparx Systems Enterprise Architect repositories stored in various database systems via ODBC, allowing AI assistants to browse and query model data without requiring Windows or a running EA instance.

Analyzes GitHub and local repositories to automatically generate visual architectural diagrams such as dependency graphs, class diagrams, and data flow diagrams.

The Fabric-Analytics-MCP server enables AI agents to interact directly with Microsoft Fabric using natural language. It transforms complex data engineering tasks—such as workspace management, data exploration, and job execution—into intuitive, conversational workflows for LLMs like Claude or GitHub

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

Generate, edit, and export data-architecture diagrams from any MCP client. Typed tables with columns, column-level lineage, real tool icons, PNG export straight back into the chat.

A tree whose vocabulary, rules and solvers are data, edited at runtime through generic tree_* tools. Rules go red on the node that breaks them, so it works as a design-dexision ledger on any checked knowledge base.

Enables automatic generation of UML class diagrams and entity-relationship diagrams from natural language descriptions or structured JSON data. It integrates with MCP agents to create visual representations of code structures and system designs without manual Mermaid coding.