"Analyzing Large Amounts of Text" matching MCP servers:

MCP server for local speech-to-text using Whisper Large V3 (MLX), enabling audio transcription with text/timestamps/SRT output and LLM-based correction, all running offline on Apple Silicon.

Gives every AI agent working in a repository a shared, persistent knowledge graph stored in a plain JSONL file, with each entity, relation, and observation tagged with the date and agent that added it. Provides tools and prompts for searching, editing, renaming, merging, cleaning up, and exporting that memory, and keeps it locked to the repository that owns it.

Delegates mechanical text-to-text tasks to a local LLM to save Claude subscription quota, reading files server-side so large content never enters Claude's context.

Provides access to Swedish Text-TV content from SVT including news, sports, weather forecasts, and TV schedules through the Model Context Protocol.

Enables text-to-speech conversion using Google Translate's TTS, supporting many languages and accents, and saving MP3 files.

Enables searching and analyzing GitHub Copilot's conversation history stored locally, providing tools for full-text search, session listing, statistics, and file-based retrieval.

Enables calculation of Simples Nacional taxes in Brazil, including DAS, effective rate, Fator R, sector exemptions, and tax amounts not covered by the DAS, helping assistants avoid incomplete or misleading tax conclusions.

Enables building client statements of account from existing invoices, credit notes, and deposits, with aged outstanding balances, PDF/plain-text output, and drafted payment chasers at friendly, firm, or final levels.

Text-to-speech MCP server that enables AI assistants to read text aloud on the user's computer using Windows SAPI, with no API key or cloud service required.

A line-oriented text file editor. Optimized for LLM tools with efficient partial file access to minimize token usage.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

Provides a tool to calculate basic text metrics including character count, characters without spaces, and word count.

Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.

Enables renters to cross-examine their rent ledger against their lease using deterministic tools, uncovering discrepancies in charges, fees, and rent amounts.

Enables extracting visible text and links from webpages for content analysis.

Enables fast text classification using Model2Vec static embeddings with 10 default categories (technology, business, health, etc.), supports custom category management, batch processing, and provides both local and remote deployment options.

Provides 9 text processing tools for analysis, sentiment, language detection, summarization, spelling, and readability tips.

Provides image understanding capabilities by analyzing single or multiple images (local files, URLs, or base64) via MiniMax VL API, complementing text-only models.

Runs 20 slash-command workflows across Google Calendar, Gmail, Linear, Slack, Granola, Google Docs, GitHub, Stripe, Notion, Google Forms, Sheets and Drive to produce morning briefs, meeting prep, action items assigned to owners and weekly updates. Reads proceed without asking, while anything that creates, sends, changes or deletes is shown for approval first.

A Model Context Protocol server that enables AI assistants to interact with Google Gemini CLI, allowing them to leverage Gemini's large token window for analyzing files and codebases using natural language commands.