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https://github.com/Shubhamsaboo/awesome-llm-apps.git
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feat: Update GitHub MCP Agent to use official GitHub MCP Server via Docker
- Replaced Node.js MCP server with the official GitHub MCP server running in Docker. - Added OpenAI API key input for enhanced query processing. - Updated README to reflect new requirements and usage instructions.
This commit is contained in:
Shubhamsaboo
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A Streamlit application that allows you to explore and analyze GitHub repositories using natural language queries through the Model Context Protocol (MCP).
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**✨ Now using the official [GitHub MCP Server](https://github.com/github/github-mcp-server) from GitHub!**
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## Features
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- **Natural Language Interface**: Ask questions about repositories in plain English
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@@ -15,11 +17,11 @@ A Streamlit application that allows you to explore and analyze GitHub repositori
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### Requirements
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- Python 3.8+
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- Node.js and npm (for MCP GitHub server)
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- This is a critical requirement! The app uses `npx` to run the MCP GitHub server
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- Download and install from [nodejs.org](https://nodejs.org/)
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- GitHub Personal Access Token with appropriate permissions
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- Docker (for official GitHub MCP server)
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- Download and install from [docker.com](https://www.docker.com/get-started)
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- Make sure Docker is running before starting the app
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- OpenAI API Key
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- GitHub Personal Access Token
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### Installation
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@@ -34,35 +36,26 @@ A Streamlit application that allows you to explore and analyze GitHub repositori
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pip install -r requirements.txt
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```
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3. Verify Node.js and npm are installed:
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3. Verify Docker is installed and running:
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```bash
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node --version
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npm --version
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npx --version
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docker --version
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docker ps
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```
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All of these commands should return version numbers. If they don't, please install Node.js.
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4. Set up your API keys:
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- Set OpenAI API Key as an environment variable:
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```bash
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export OPENAI_API_KEY=your-openai-api-key
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```
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- GitHub token will be entered directly in the app interface
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5. Create a GitHub Personal Access Token:
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- Visit https://github.com/settings/tokens
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- Create a new token with `repo` and `user` scopes
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- Save the token somewhere secure
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4. Get your API keys:
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- **OpenAI API Key**: Get from [platform.openai.com/api-keys](https://platform.openai.com/api-keys)
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- **GitHub Token**: Create at [github.com/settings/tokens](https://github.com/settings/tokens) with `repo` scope
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### Running the App
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1. Start the Streamlit app:
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```bash
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streamlit run app.py
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streamlit run github_agent.py
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```
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2. In the app interface:
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- Enter your GitHub token in the sidebar
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- Enter your OpenAI API key
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- Enter your GitHub token
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- Specify a repository to analyze
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- Select a query type or write your own
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- Click "Run Query"
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@@ -7,19 +7,21 @@ from agno.tools.mcp import MCPTools
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from mcp import ClientSession, StdioServerParameters
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from mcp.client.stdio import stdio_client
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# Page config
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st.set_page_config(page_title="🐙 GitHub MCP Agent", page_icon="🐙", layout="wide")
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# Title and description
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st.markdown("<h1 class='main-header'>🐙 GitHub MCP Agent</h1>", unsafe_allow_html=True)
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st.markdown("Explore GitHub repositories with natural language using the Model Context Protocol")
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# Setup sidebar for API key
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with st.sidebar:
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st.header("🔑 Authentication")
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openai_key = st.text_input("OpenAI API Key", type="password",
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help="Required for the AI agent to interpret queries and format results")
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if openai_key:
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os.environ["OPENAI_API_KEY"] = openai_key
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github_token = st.text_input("GitHub Token", type="password",
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help="Create a token with repo scope at github.com/settings/tokens")
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if github_token:
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os.environ["GITHUB_TOKEN"] = github_token
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@@ -41,7 +43,6 @@ with st.sidebar:
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st.markdown("---")
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st.caption("Note: Always specify the repository in your query if not already selected in the main input.")
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# Query input
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col1, col2 = st.columns([3, 1])
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with col1:
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repo = st.text_input("Repository", value="Shubhamsaboo/awesome-llm-apps", help="Format: owner/repo")
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@@ -50,7 +51,6 @@ with col2:
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"Issues", "Pull Requests", "Repository Activity", "Custom"
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])
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# Create predefined queries based on type
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if query_type == "Issues":
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query_template = f"Find issues labeled as bugs in {repo}"
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elif query_type == "Pull Requests":
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@@ -63,25 +63,34 @@ else:
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query = st.text_area("Your Query", value=query_template,
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placeholder="What would you like to know about this repository?")
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# Main function to run agent
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async def run_github_agent(message):
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if not os.getenv("GITHUB_TOKEN"):
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return "Error: GitHub token not provided"
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if not os.getenv("OPENAI_API_KEY"):
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return "Error: OpenAI API key not provided"
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try:
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server_params = StdioServerParameters(
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command="npx",
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args=["-y", "@modelcontextprotocol/server-github"],
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command="docker",
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args=[
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"run", "-i", "--rm",
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"-e", "GITHUB_PERSONAL_ACCESS_TOKEN",
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"-e", "GITHUB_TOOLSETS",
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"ghcr.io/github/github-mcp-server"
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],
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env={
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**os.environ,
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"GITHUB_PERSONAL_ACCESS_TOKEN": os.getenv('GITHUB_TOKEN'),
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"GITHUB_TOOLSETS": "repos,issues,pull_requests"
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}
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)
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# Create client session
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async with stdio_client(server_params) as (read, write):
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async with ClientSession(read, write) as session:
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# Initialize MCP toolkit
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mcp_tools = MCPTools(session=session)
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await mcp_tools.initialize()
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# Create agent
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agent = Agent(
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tools=[mcp_tools],
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instructions=dedent("""\
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@@ -93,24 +102,25 @@ async def run_github_agent(message):
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- Include links to relevant GitHub pages when helpful
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"""),
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markdown=True,
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show_tool_calls=True,
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)
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# Run agent
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response = await agent.arun(message)
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response = await asyncio.wait_for(agent.arun(message), timeout=120.0)
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return response.content
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except asyncio.TimeoutError:
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return "Error: Request timed out after 120 seconds"
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except Exception as e:
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return f"Error: {str(e)}"
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# Run button
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if st.button("🚀 Run Query", type="primary", use_container_width=True):
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if not github_token:
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if not openai_key:
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st.error("Please enter your OpenAI API key in the sidebar")
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elif not github_token:
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st.error("Please enter your GitHub token in the sidebar")
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elif not query:
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st.error("Please enter a query")
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else:
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with st.spinner("Analyzing GitHub repository..."):
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# Ensure the repository is explicitly mentioned in the query
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if repo and repo not in query:
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full_query = f"{query} in {repo}"
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else:
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@@ -118,32 +128,30 @@ if st.button("🚀 Run Query", type="primary", use_container_width=True):
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result = asyncio.run(run_github_agent(full_query))
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# Display results in a nice container
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st.markdown("### Results")
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st.markdown(result)
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# Display help text for first-time users
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if 'result' not in locals():
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st.markdown(
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"""<div class='info-box'>
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<h4>How to use this app:</h4>
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<ol>
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<li>Enter your GitHub token in the sidebar</li>
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<li>Enter your <strong>OpenAI API key</strong> in the sidebar (powers the AI agent)</li>
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<li>Enter your <strong>GitHub token</strong> in the sidebar</li>
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<li>Specify a repository (e.g., Shubhamsaboo/awesome-llm-apps)</li>
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<li>Select a query type or write your own</li>
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<li>Click 'Run Query' to see results</li>
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</ol>
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<p><strong>Important Notes:</strong></p>
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<p><strong>How it works:</strong></p>
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<ul>
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<li>The Model Context Protocol (MCP) provides real-time access to GitHub repositories</li>
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<li>Queries work best when they focus on specific aspects like issues, PRs, or repository info</li>
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<li>More specific queries yield better results</li>
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<li>This app requires Node.js to be installed (for the npx command)</li>
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<li>Uses the official GitHub MCP server via Docker for real-time access to GitHub API</li>
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<li>AI Agent (powered by OpenAI) interprets your queries and calls appropriate GitHub APIs</li>
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<li>Results are formatted in readable markdown with insights and links</li>
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<li>Queries work best when focused on specific aspects like issues, PRs, or repository info</li>
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</ul>
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</div>""",
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unsafe_allow_html=True
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)
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# Footer
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st.markdown("---")
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st.write("Built with Streamlit, Agno, and Model Context Protocol ❤️")
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st.write("Built with Streamlit, Agno, and Model Context Protocol ❤️")
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