Full readme incoming
MCP.Pizza Chef: JackalLabs
Jackal MCP is a client implementation of the Model Context Protocol (MCP) designed to enable agentic AI capabilities. Built natively with Anthropic MCP, it orchestrates context flow and tool interactions for AI models, facilitating real-time, multi-step reasoning and environment interaction. It serves as a bridge between LLMs and various MCP servers, enhancing AI workflows with secure, scoped, and observable interactions.
Use This MCP client To
Coordinate multi-step AI reasoning workflows Manage context flow between AI models and MCP servers Integrate agentic AI capabilities into applications Orchestrate tool usage for AI-driven tasks Enable real-time environment interaction for AI agents
README
jackal-mcp FAQ
How does Jackal MCP client interact with MCP servers?
It manages context flow and tool calls between AI models and MCP servers, enabling seamless integration.
Can Jackal MCP client work with multiple LLM providers?
Yes, it is provider-agnostic and supports models like Anthropic, OpenAI, and Claude.
What programming languages is Jackal MCP client compatible with?
It is designed to be flexible and can be integrated with various languages depending on implementation.
Is Jackal MCP client secure for production use?
Yes, it follows MCP principles for secure, scoped, and observable model interactions.
Does Jackal MCP client support real-time context updates?
Yes, it enables real-time feeding of structured context to AI models for dynamic reasoning.
How can developers extend Jackal MCP client?
Developers can add custom tool orchestration and context management logic to fit specific workflows.
Is Jackal MCP client open source?
Yes, it is available on GitHub under Jackal's repository for community use and contributions.