"JSON File Upload, Data Vectorization, and LLM Similarity Search" matching MCP servers:

JSON Contracts is a local MCP server for transforming natural language into Git-controlled JSON contracts, JSON Schema validation, and structured LLM/agent outputs.

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.

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

Reduces Claude's context window costs by automatically summarizing inactive files to their public interfaces using AST parsing, keeping only the full contents of the currently active file.

Enables AI agents to explore, analyze, and search file systems, with tools for directory trees, file statistics, duplicate detection, code counting, and multi-criteria file search.

Enables coding agents to inspect Python applications, research source and target models, and produce reviewable migration plans with evidence gates and evaluation before production code changes.

An MCP server that provides a flexible lens into directory structures and files, enabling LLM clients to efficiently navigate and understand codebases with minimal noise. It offers secure, gitignore-aware file access with tools like directory listing, file reading, and grep-like search.

Enables precise file patching using SEARCH/REPLACE blocks, with mandatory directory sandboxing, automatic Python QA (Ruff/Black/MyPy), and git versioning for rollback.

MCP server for reviewing code changes using LLMs, supporting Copilot, Ollama, and OpenAI-compatible endpoints.

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.

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.

Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.

Provides deep git file-level forensics tools to analyze detailed file histories, changes, and patterns within git repositories, focusing on individual file analysis rather than repository-wide operations.

MCP server that exposes an AI decompiler via an OpenAI-compatible API, enabling decompilation, explanation, and variable renaming of disassembly for binary analysis.

Bridges local LLMs running in LM Studio with MCP clients like Claude Desktop to perform reasoning and analysis tasks while keeping sensitive data private. It features a suite of tools for local code review, privacy scanning, and content transformation using auto-discovered local models.

MCP server exposing a shared pr-review skill with tools to list, get, run, and evaluate skills, enabling AI assistants to perform code review tasks.

Enables semantic code search across indexed code folders using vector embeddings, with support for multiple embedding providers and automatic file watching. Provides an admin UI and integrates with MCP clients for natural language code queries.

Semantic + lexical code search as an MCP server. Agents query in natural language and get back ranked file:line ranges to read precisely.