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@@ -225,6 +231,15 @@ Programmatically assemble prompts for LLMs using [GenAIScript](https://microsoft
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- Goose allows you to extend its functionality by [building your own MCP servers](https://block.github.io/goose/docs/tutorials/custom-extensions).
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- Includes built-in tools for development, web scraping, automation, memory, and integrations with JetBrains and Google Drive.
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### gptme
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[gptme](https://github.com/gptme/gptme) is a open-source terminal-based personal AI assistant/agent, designed to assist with programming tasks and general knowledge work.
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**Key features:**
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- CLI-first design with a focus on simplicity and ease of use
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- Rich set of built-in tools for shell commands, Python execution, file operations, and web browsing
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- Local-first approach with support for multiple LLM providers
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- Open-source, built to be extensible and easy to modify
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### Klavis AI Slack/Discord/Web
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[Klavis AI](https://www.klavis.ai/) is an Open-Source Infra to Use, Build & Scale MCPs with ease.
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- Open-source and self-hostable, with secure multi-user support
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- Future roadmap includes expanded MCP feature support
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### Lutra
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[Lutra](https://lutra.ai) is an AI agent that transforms conversations into actionable, automated workflows.
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**Key features:**
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- Easy MCP Integration: Connecting Lutra to MCP servers is as simple as providing the server URL; Lutra handles the rest behind the scenes.
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- Chat to Take Action: Lutra understands your conversational context and goals, automatically integrating with your existing apps to perform tasks.
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- Reusable Playbooks: After completing a task, save the steps as reusable, automated workflows—simplifying repeatable processes and reducing manual effort.
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- Shareable Automations: Easily share your saved playbooks with teammates to standardize best practices and accelerate collaborative workflows.
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**Learn more:**
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-[Lutra AI agent explained](https://www.youtube.com/watch?v=W5ZpN0cMY70)
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### mcp-agent
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[mcp-agent] is a simple, composable framework to build agents using Model Context Protocol.
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- Extend Copilot Studio agents with MCP servers
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- Leveraging Microsoft unified, governed, and secure API management solutions
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### MindPal
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[MindPal](https://mindpal.io) is a no-code platform for building and running AI agents and multi-agent workflows for business processes.
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**Key features:**
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- Build custom AI agents with no-code
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- Connect any SSE MCP server to extend agent tools
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- Create multi-agent workflows for complex business processes
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- User-friendly for both technical and non-technical professionals
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- Ongoing development with continuous improvement of MCP support
specification to indicate the locations of authorization servers. The Protected Resource Metadata document returned by the MCP server **MUST** include
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the `authorization_servers` field containing at least one authorization server.
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The specific use of `authorization_servers` is beyond the scope of this specification; implementers should consult
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OAuth 2.0 Protected Resource Metadata ([RFC9728](https://datatracker.ietf.org/doc/html/rfc9728)) for
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OAuth 2.0 Protected Resource Metadata ([RFC9728](https://datatracker.ietf.org/doc/html/rfc9728)) for
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guidance on implementation details.
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Implementors should note that Protected Resource Metadata documents can define multiple authorization servers. The responsibility for selecting which authorization server to use lies with the MCP client, following the guidelines specified in
MCP servers **MUST** use the HTTP header `WWW-Authenticate` when returning a _401 Unauthorized_ to indicate the location of the resource server metadata URL
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as described in OAuth 2.0 Protected Resource Metadata ([RFC9728](https://datatracker.ietf.org/doc/html/rfc9728)).
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