"Historical cryptocurrency market data" matching MCP servers:

Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.

A Model Context Protocol server that enables Claude to load CSV files and execute JavaScript data analysis scripts for advanced data exploration and insights generation.

Enables Claude Code to work with personal data that stays on the local machine, running SQL, Python, and file/schema inspection in a sandboxed compute-to-data setup that returns only aggregates, schemas, synthetic fixtures, and pseudonymized results. Raw records, file names, and protected values never reach the Anthropic API, so Auto mode can stay hands-off.

An MCP server that provides data bridging from Spring Boot interfaces and a lightweight Python sandbox for script execution. It enables agents to fetch data as Markdown or Parquet files and perform automated data analysis within a controlled environment.

Enables secure execution of statistical Python code in isolated micro-VM sandboxes, generating charts and analytical summaries.

This server integrates with the fastmcp library to expose the full range of NebulaBlock API functionalities as accessible tools, enabling seamless and efficient interaction within any MCP-compatible environment.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

Enables AI to create and manage MQL5 source files, compile them via MetaEditor's CLI, and run historical backtests through MetaTrader 5's Strategy Tester within a sandboxed MQL5 folder.

Enables MCP-compatible AI agents to access Polymarket prediction-market data and run Python 3.12 in an isolated sandbox, with each call paid automatically in USDC on Base.

An advanced MCP server for real-time worldwide stock market data, technical indicators, financials, news, and Python sandboxing with AI models, supporting US and Indian markets.

Enables AI assistants to interact with Interactive Brokers trading accounts to retrieve market data, check positions, and place trades. Includes pre-configured IB Gateway and handles OAuth authentication automatically.

An MCP server for integrating with Zerodha Kite API that provides Claude with tools to interact with your Kite trading account, enabling portfolio management, market data access, and order execution.

A Model Context Protocol (MCP) server that provides AI assistants with access to Shioaji trading API for the Taiwanese financial market.

Enables AI assistants to interact with the MetaTrader 5 trading platform for market data analysis, placing trades, and managing trading positions. Provides comprehensive access to forex and financial market operations through the Model Context Protocol.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

Enables AI agents to interact with Bentley STAAD.Pro models for tasks like load case definition, data extraction, and property setting through natural language.

Lets Claude write and run short JavaScript programs against the YouTube Data, Analytics, and Reporting APIs, plus transcripts and search autocomplete, so multi-step channel tasks like joining upload stats with analytics finish in a single round trip. Code executes in a sandboxed isolate with quota tracking and confirmation gates for destructive or public actions.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.