"Files formatted in JSON" matching MCP servers:

Query only the data you need from your JSON file and keep your context clean

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.

Enables saving and managing files in a sandboxed local folder via MCP, with tools for listing, reading, writing, appending, searching, moving, and deleting files and directories.

A Model Context Protocol server that enables creating, modifying, and validating infinite canvas data structures according to the JSON Canvas 1.0 specification.

A Model Context Protocol server that provides API functionality for creating, managing, and exporting Excalidraw drawings in various formats like SVG, PNG, and JSON.

Converts JSON data to TOON (Token-Oriented Object Notation) format and back, reducing token usage by 30-60% for more efficient LLM applications.

MCP server for Python JSON logs

A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files, enabling extraction of data from entire workbooks or specific sheets with results returned in structured JSON format.

A Model Context Protocol server that allows creation and management of multiple Fireproof JSON databases with CRUD operations, querying capabilities, and cloud synchronization for sharing databases with others.

Enables searching for files by name fragments via JSON-RPC or an HTTP REST API, with options for direct use or integration with other tools like VS Code.

A Model Context Protocol (MCP) server for converting files between different formats

Enables deep, order-independent comparison of JSON files to detect differences including missing keys, value mismatches, and type differences. Provides detailed reports with path tracking for precise identification of variations between JSON structures.

Enables AI agents to search, inspect, and retrieve Irish Central Statistics Office PxStat datasets through MCP tools. Supports catalog search, metadata discovery, full-table reads, and filtered JSON-stat queries.

Provides deterministic JSON repair and JSON Schema validation for malformed AI agent outputs, safely fixing unambiguous errors without an LLM and refusing ambiguous cases.

Aggregates multiple MCP services into a single unified interface with self-configuration capabilities, enabling dynamic addition and removal of tools via conversation.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

Deterministic JSON validation and repair for AI agents. Validates, repairs, schema-checks, and diffs JSON so long-running agents don't corrupt their session state with malformed writes.

Persistent memory and pattern learning for AI coding assistants via MCP.

Provides powerful JSON manipulation tools through Model Context Protocol, enabling complex queries, schema generation, and validation with jq notation and native Node.js operations.