"Files formatted in JSON" matching MCP servers:

Enables efficient JSON file editing with targeted read, write, delete, and deep merge operations using dot notation paths, optimized for managing multilingual projects and large configuration files.

Enables ChatGPT/Codex to read, search, and edit files in a single allowed folder on Windows through OpenAI Secure MCP Tunnel.

MCP server for reading, querying, and filtering local JSON files with extended JSONPath syntax, supporting sorting, aggregations, and complex conditions.

A local MCP server that enables AI agents to securely read, write, search, and edit JSON and Markdown files through a gated permission-scoped interface with configurable access modes.

Enables efficient navigation and search of large JSON files (>10MB) through intelligent path exploration and fuzzy search capabilities, designed to save tokens by avoiding loading entire files into context.

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

Enables reading, searching, editing, and writing files in legacy encodings such as GBK, Big5, Shift-JIS, and Windows codepages, with automatic detection and preservation of the original encoding.

Enables coding agents to extract verbatim, intent-relevant spans from large low-density files like logs, CSV, JSON, and HTML, verified against the original file to reduce context usage.

MCP server that gives AI chat real vision by reading images, files, logs, and zip archives via local OCR in any language, with privacy-first processing.

Enables read-only SQL querying and exploration of data files (CSV, Parquet, JSON, Excel, etc.) via DuckDB, supporting local paths, globs, URLs, and S3 buckets.

Enables AI assistants to inspect, create, and report on IFC/BIM files locally, and to open models in a viewer with BCF viewpoint support.

Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.

MCP server for AI-powered resume optimization and generation. It enables clients to optimize existing resumes or generate new ones from background info via LLM, producing formatted .docx and .pdf files.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

Enables LLM agents to find and safely delete duplicate files using content-based detection, with smart copy prioritization and dry-run mode.

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.

Enforces mandatory human approval before LLM agents can edit files, create files, or execute shell commands, using session tokens and audit logging.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Enables AI agents to read and extract text, tables, and image content from files (PDF, DOCX, PPTX, SVG, PNG) within a folder, providing structured data for interpretation by the calling model.

Enables AI assistants to safely manage Pterodactyl game servers, covering status, console, files, backups, and power operations with built-in guardrails.