"How to modify local files" matching MCP servers:

Enables uploading local files to Slack with a message, supporting channels, DMs, threads, and file titles.

Lets MCP clients delegate private or bulk text tasks to a local OpenAI-compatible LLM while keeping data on the machine.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

Enables Claude to fetch web pages from the user's own local network connection instead of AI datacenter IPs, including optional authenticated sessions, with verdicts for bot challenges, login walls, and other failures.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables local conversion of PDFs to Markdown, with automatic OCR fallback for scanned pages, image extraction, and page-by-page structure preservation.

Evaluates task suitability for local models before cloud API calls, routing to Ollama or similar to reduce costs.

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

Provides AI agents with accurate current time and date, including the Jalali (Persian) calendar, timezone-aware with automatic DST handling, via an MCP server.

A token-efficient, schema-aware MCP server that enables AI assistants to safely read, modify, query, and validate JSON, YAML, and TOML files with automatic schema detection and format conversion capabilities.

Convert PDFs to structured JSON. Extract invoices, bank statements, contracts, and more. Pay per call via x402 USDC.

Enables AI agents to search, read, annotate, and manage a local Zotero library via the Model Context Protocol, with full local storage and no cloud dependency.

Provides a stateful local Spark session for running PySpark and SQL cells, enabling local data exploration before deploying to Microsoft Fabric.

Persistent local semantic memory for MCP tools, enabling storing and searching notes by meaning using local embeddings and SQLite.

Enables AI coding agents to safely execute commands, run tests, and modify project files inside disposable, policy-enforced Docker sandboxes that are isolated from the host machine and its credentials.

A read-only MCP server that lets AI search and read both sides of a user's own LINE Desktop chat history on macOS using local database snapshots, without needing a LINE Official Account or altering unread state.

Enables local document search and reading across formats like docx, pdf, md, and more, providing tools for listing, searching, and reading documents.

Enables cloud-based MCP clients to delegate privacy-sensitive or large-output tasks to a local LLM, returning sanitized placeholders or digested summaries so private data never leaves the user's network.

A read-only MCP server that lets AI search a user's own LINE Desktop chat history on macOS, providing tools to list chats, retrieve messages, and search conversations directly from the local encrypted database.

Local-only MCP server for saving and restoring conversation context across AI agent sessions using JSON files on disk.