"Excel data processing tutorials and techniques" matching MCP servers:

An MCP server that provides a semantic index and 14 bounded tools for AI agents to navigate Excel workbooks by symbols, references, and diagnostics, avoiding the need to read entire rows.

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

Enables teams to structure metric definitions, compare semantic differences, detect JOIN fanout and drift, reconcile mismatched numbers layer by layer, and persist metric contracts as YAML.

Read, write, analyze and test the VBA inside Excel, Word, PowerPoint and Access files, and edit the document around it. The file layer needs no Office installation and runs anywhere; running macros and tests needs Windows with Office.

Enables AI agents to analyze and diff binaries by driving Ghidra headless or inside its GUI, exposing native reverse-engineering tools such as listing functions and segments, searching strings, decompiling, disassembling, and following cross-references. Ships with a devcontainer and supports local stdio or remote HTTP deployment.

Enables MCP clients to load eight on-demand coding skills and inspect project repositories through bounded, read-only map, search, read, diff, checks, and style tools. It keeps context lean by loading skill bodies only when needed and limiting repository scan and output sizes.

Enables efficient analysis of large codebases using Claude Code and Kimi K2.5 through the Model Context Protocol, with session caching and parallel processing to reduce costs and time.

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Routes narrow text-processing tools (classification, extraction, summarization, etc.) to budget models to reduce token consumption on the main model.

Professional Gemini API integration for Claude and MCP-compatible hosts with intelligent model selection and advanced file handling capabilities.

A feature-rich MCP server offering 30 tools across AI, code, text, data, web, and system categories, enabling tasks like chat, translation, code review, web scraping, and text processing.

Enables AI assistants to inspect, refactor, lint, run, and version Power Query (M) queries in Excel workbooks and Power BI projects, with snapshot safety and live evaluation.

Gives coding agents source-grounded Apple developer knowledge by searching an index of WWDC20–WWDC26 sessions, Apple documentation, tutorials, Human Interface Guidelines, Swift Evolution, and App Store Review Guidelines. Enables API availability and deprecation lookups, transcript and "what changed" queries, guideline checks, and repo-level Swift app audits through 45 read-only tools.

A Model Context Protocol server that analyzes and evaluates GitHub README documentation quality using advanced neural processing, providing scores and improvement suggestions.

A MCP server that transforms code repositories from GitHub, GitLab, or local directories into LLM-friendly formats, preserving context and structure for better AI processing.

Connects MCP-enabled editors to GitHub Copilot CLI for non-interactive code analysis, batch processing, and code review.

Enables AI coding agents to index local codebases and search them by natural-language intent, find related files through imports and semantic similarity, and check indexing status. All processing runs locally via MCP tools.

A server-side implementation that handles context processing between GitHub repositories and AI models, enabling seamless integration of AI capabilities with codebases through the Model Context Protocol.

Exposes all major ILSpy CLI features as separate MCP tools for decompiling .NET assemblies, enabling automated end-to-end processing and structured JSON reports.