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google-labs-jules bot and others added 7 commits May 22, 2025 01:37
This commit refactors the location of the AI Agents documentation.

- I created a new `ai-agents/` directory in the root.
- I moved the content from `details/ai-agents.md` to `ai-agents/README.md`.
- I updated the link in `README-details.md` to point to the new location (`./ai-agents/`).

This addresses your feedback to have a dedicated folder for the AI Agents section.
refactor: Move AI Agents section to its own directory
This commit introduces a new file containing a curated list of Model-Control-Presenter (MCP) frameworks, tutorials, and tools relevant to AI agent development.

- Created a new subdirectory `ai-agents/resources/`.
- Added a new file `ai-agents/resources/mcp-tutorials-tools.md` with the list of resources.
- Each resource includes a short description and a direct link.
- Added a link to this new resource list in `ai-agents/README.md` under an "Additional Resources" section.

This addresses your request for a dedicated list of relevant MCPs, tutorials, and tools.
This commit implements the following changes:

- Moved the content from `ai-agents/resources/mcp-tutorials-tools.md` to `ai-agents/resources/README.md`.
- Updated the link in `ai-agents/README.md` to point to the new resource file location (`./resources/`).
- Restructured `ai-agents/resources/README.md`:
    - Created a new dedicated top-level section "MCP Servers".
    - Moved all MCP server implementations (including Bary Huang's projects and mcp-bridge) under this new section.
    - Ensured other content remains well-organized.

These changes improve the organization and discoverability of the AI agent resources.
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Looks great to me!

@ji-podhead
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supabase and playwright mcps are really useful from what i have heard.

@ji-podhead
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ji-podhead commented May 22, 2025

then we also need an example how to use toolcalls with gemini, or litellm.

@ji-podhead
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I will also share this with multiple discord groups to ask people about their most liked tools.
I also think that docker mcp toolkit is missing .

@ji-podhead
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mcp python client https://modelcontextprotocol.io/docs/concepts/transports#python-client
with http transport:

async with sse_client("http://localhost:8000/sse") as streams:

    async with ClientSession(streams[0], streams[1]) as session:
        await session.initialize()

with stdio

params = StdioServerParameters(
    command="./server",
    args=["--option", "value"]
)
async with stdio_client(params) as streams:
    async with ClientSession(streams[0], streams[1]) as session:
        await session.initialize()

i have a lot more

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2 participants