"A tool for editing files" matching MCP servers:

基于Model Context Protocol (MCP) 的A股实时行情查询服务器，支持查询A股实时价格、历史K线数据、财务信息及市场概况。

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

Lets an AI agent pull the user's own Douyin creator-backend work data — plays, likes, comments, shares, saves, 5-second completion rate and more — into a locally accumulating CSV plus a daily overview, with tools for status checks, fetching, merging, and retrospective analysis. Access is read-only to the user's own account, needs no third-party dependencies, and keeps all data on the local machine.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

A read-only MCP server that reports BI pipeline readiness, blockers, and the next allowed action for governed Power BI workflows. It never writes files, executes warehouse work, or grants human approvals.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

Enables interaction with Telegram chat history, including text, photos, and documents, via the GramJS MTProto userbot. It provides tools for searching chats, syncing message history, and downloading media files for local analysis.

Connect Claude to your Power BI semantic models. Browse workspaces, tables, and measures, run DAX queries, and get results — with large datasets automatically saved to local CSV files to protect the LLM context window. Includes a query history log for cross-session reuse and auditability.

Read-only SQL across PostgreSQL, MySQL, S3-compatible buckets and folders of Parquet, CSV and JSON files — and one query can join across all of them, federated in-process by DuckDB. Sources are given as connection strings at startup, and no tool writes: they are absent rather than disabled.

Enables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.

Enables AI agents to perform professional-grade geoprocessing tasks such as buffers, overlays, reprojections, and terrain analysis with deterministic tools and verifiable provenance.

Enables AI agents to work with a real Excel-compatible spreadsheet engine, allowing them to create and manipulate structured data blocks, write and evaluate formulas, and save genuine .xlsx files with live formulas for human verification and reuse.

Generates formatted Excel (.xlsx) files from user requests and deposits them into Cleyrop project data.

Creates compact skeleton representations of large JSON files by preserving structure while truncating string values and deduplicating arrays, helping users understand JSON structure without processing the full data payload.

Turns a folder of CSV, Parquet, and JSON files into a single SQL-queryable source for AI agents, supporting JOINs across files with read-only sandboxed access.

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.

Enables comprehensive analysis of CSV files and SQLite databases through tools for statistics, correlations, anomaly detection, pivot tables, time series analysis, visualization, and automated insights discovery.

It gives Claude Code, Cursor, and Codex structured workflows and an MCP server for building data pipelines with dlt - covering REST API ingestion, transformations, data quality, and exploration.

Enables users to convert structured data into Token-Oriented Object Notation (TOON) to reduce LLM token usage and costs by up to 70%. It provides tools for encoding, decoding, and analyzing data formats like JSON, CSV, and XML to optimize prompt efficiency.