"Understanding File Usage" matching MCP servers:

A tutorial implementation MCP server that enables analysis of CSV and Parquet files. Allows users to summarize data and query file information through natural language interactions.

An MCP server for the Octopus Energy Japan GraphQL API that allows users to retrieve electricity consumption, cost estimates, and contract details. It enables 30-minute interval usage analysis and postal code area searches while ensuring privacy by excluding personal address information.

Enables efficient extraction of specific data from JSON APIs using JSONPath patterns, reducing token usage by up to 99% compared to fetching entire responses. Supports single and batch operations for both JSON extraction and raw text retrieval from URLs.

Converts JSON data to TOON (Token-Oriented Object Notation) format and back, reducing token usage by 30-60% for more efficient LLM applications.

Provides efficient handling of large Excel files through automatic chunking and pagination, using MCP to enable seamless file reading and management features such as sheet selection and error handling.

Enables AI assistants to look up FIRE data standard fields, validate draft records, and receive mapping suggestions when mapping internal data formats onto FIRE.

Enables AI applications to interact with decentralized storage through a standardized Model Context Protocol interface, allowing file uploads, retrievals, and identity management.

This read-only MCP Server allows you to connect to CSV Files data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for CSV Files (https://www.cdata.com/drivers/csv/download/mcp).

MCP server that gives AI assistants direct access to RaceHooks motorsport analytics and data, enabling management of webhooks, live sessions, simulations, and account usage.

Converts JSON data and system prompts to and from TOON (Token-Oriented Object Notation) format, reducing token usage by 30-60% when interacting with LLMs while preserving data structure.

Converts legacy supply chain databases and file drops into MCP servers for AI agents, enabling direct interaction with closed systems via CLI.

Provides system utilities, file operations, data tools, creative idea generation, and dynamic resources via MCP, with auth support for bearer tokens and OAuth.

A Python-based MCP server that collects, analyzes, and visualizes forest fire occurrence data on maps, allowing users to access regional fire information, risk analysis, and map visualizations.

A tiny remote MCP server with a single tool, drop, that saves a file from local content or a URL into a mounted directory, acting as a file dropper for watch-folder importers.

MCP server for converting between everyday file formats (CSV, Excel, Markdown, Word), including a GxP-compliant Markdown to Word template. Exposes four conversion tools over stdio.

Provides deterministic tools for understanding, transforming, and verifying structured data via MCP, enabling rule inference from examples and verification of transformed records.

Enables CRUD operations on NocoDB tables via natural language commands, supporting table manipulation, file upload, and bulk actions.

Exposes SAP BW/4HANA ADT operations as MCP tools for LLM clients, with a local-file buffering layer to handle large XML payloads and table data efficiently.

Paid remote MCP endpoint for AI SDK data queries, offering structured JSON tools, token-based access, usage receipts, and audit-ready workflow evidence.

Exposes an agentic AutoML pipeline as a callable tool so any MCP client can upload a CSV and natural language goal and receive a full ML analysis report with SHAP visualizations. Enables autonomous problem understanding, data cleaning, feature engineering, model training, and explainability through a single remote tool call.