A state-based agent orchestration system that allows transitions between different states (IDLE, PLANNING, RESEARCHING, EXECUTING, REVIEWING, ERROR) while maintaining conversation context and providing state-specific prompts.
A Model Context Protocol implementation that enables LLMs to execute complex, multi-step workflows combining tool usage with cognitive reasoning, providing structured, reusable paths through tasks with advanced control flow.
Executes Python code in isolated rootless containers while proxying MCP server tools, reducing context overhead by 95%+ and enabling complex multi-tool workflows through sandboxed code execution.
Enables AI agents to write and execute Python code in an isolated sandbox that can orchestrate multiple MCP tool calls, reducing context window bloat and improving efficiency for complex workflows.
Converts JSON data and system prompts to and from TOON (Token-Oriented Object Notation) format, reducing token usage by 30-60% when interacting with LLMs while preserving data structure.
An advanced integrated MCP server platform that combines 600+ tools and multiple biomedical databases to enable comprehensive information retrieval across molecules, proteins, genes, and diseases for accelerating therapeutic research.
A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.
Provides advanced document search and processing capabilities through vector stores, including PDF processing, semantic search, web search integration, and file operations. Enables users to create searchable document collections and retrieve relevant information using natural language queries.
This server provides a comprehensive integration with Zendesk. Retrieving and managing tickets and comments. Ticket analyzes and response drafting. Access to help center articles as knowledge base.
A Model Context Protocol server that enables fetching and processing images from URLs, local file paths, and numpy arrays, returning them as base64-encoded strings with proper MIME types.
