Jinni Bring Your Project Into Context

Enhance large language model capabilities with a unified interface for intelligent context management, multi-provider AI model coordination, and seamless integration of diverse development and automation tools through a robust, scalable Model Context Protocol platform.

Provides tools for structuring and extracting data from text using JSON templates with placeholders, enabling intelligent transformation of AI-generated text into nested, structured JSON formats for seamless downstream integration under the Model Context Protocol.

Enables querying and analyzing CloudZero cloud cost data via Model Context Protocol, offering tools for billing insights, budget listing, and cost retrieval through seamless integration with Large Language Models.

Provides Model Context Protocol (MCP) support for Large Language Models by enabling efficient file system access, advanced code analysis, real-time file watching, smart caching, and powerful regex-based search with metadata and quality metrics.

Automates recursive scanning and concatenation of text files from codebases, respecting .gitignore rules and supporting chunked output for seamless integration with Model Context Protocol (MCP) clients to enhance large language model context handling.