"Files formatted in JSON" matching MCP servers:

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.

Legal document redlining engine that applies AI-generated JSON changes as professional tracked changes with comments in .docx files, producing Word-indistinguishable output.

Search Brazilian jurisprudence on JusBrasil in natural language and retrieve formatted citations for legal documents, including metadata extraction from court decisions.

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 exporting data from databases to files (CSV, TSV, JSON, BSON, Parquet, XLSX, Binary) with optional cloud storage targets, via a two-step preview-execute safety process.

An MCP server that allows AI assistants to send formatted text, files, and updates to Telegram topics, and to capture incoming messages from work chats into a local inbox for retrieval.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

MCP server for Python JSON logs

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Enables access to Australian real estate data through the Realty In Au API, supporting property listings, agent/agency information, property details, school lookups, and property search with various filters.

Provides 32 local tools for managing briefs, dispatch, run events, registry, and redaction in AI-assisted workflows, operating entirely on local markdown/JSON files with no network calls.

A MCP server that allows searching for files in the filesystem based on path fragments, returning file metadata including name, path, size, and creation date.

Enables users to access the Realty In Ca1 API to search for residential and commercial property listings, view detailed property information, and retrieve neighborhood demographics or statistics. It supports filtering by geographic location, price range, building type, and other real estate characteristics.

Enables downloading content from various social media platforms through a unified API. Provides a single tool to download media from multiple social networks using the Social Download All In One service.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

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.