"Methods for Reading Water Sensor Data" matching MCP servers:

Enables local EPUB reading with AI agents, supporting annotations, parallel editions, and MCP tools.

A 4-stage reading companion that helps users set reading goals, discover books, track progress, and deepen learning through reflection, integrated with Claude Desktop.

An advanced MCP server powered by PHREEQC for industrial wastewater treatment modeling, offering 17 tools for chemical equilibrium, kinetic reactions, and optimization like lime softening and phosphorus removal.

A Node.js application that provides a JSON-RPC interface to interact with CO2 sensor data, working in both simulation mode and with real Raspberry Pi Pico hardware connections.

Enables Claude Code or Codex CLI to see the exact sentence and section you are viewing in Chrome, so you can discuss books with context, take notes, and track reading progress.

An MCP server for COMSOL Multiphysics that enables AI agents to perform flexible pressure sensor simulation, including DXF analysis, contact model building, parameter sweeping, and result export using natural language.

Fits a lithium-ion full-cell dual-water-tank model from charge/discharge voltage-capacity data for battery aging mechanism identification, with parameter fitting, batch processing, and MCP server integration.

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 low-token human-AI co-reading MCP tool that imports local EPUB/TXT/Markdown books into chunks, enabling AI to read only relevant fragments and write co-reading results to long-term reading notes and progress files.

Enables AI assistants to print and manage 58mm thermal water bill receipts, including previewing, customizing, and printing receipts for an EPPOS EP5821 printer.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

Enables exporting Apple Safari Reading List entries to JSON and adding new items via MCP on macOS.

Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Enables local analysis of scientific papers including PDF parsing, mathematical formula extraction with AST generation, PyTorch code generation from methodology, and automated Markdown report generation with visualizations.

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.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.

MCP server for Japanese public business data, enabling AI agents to validate and look up corporate numbers, search bank/branch codes, and check national holidays. Runs locally with no telemetry; live corporate registry data requires a free NTA app ID.