awslabs/mcp
Apr 2025 – Apr 2025
1 Month active
Languages Used
Python
Technical Skills
API DevelopmentAWS BedrockBackend DevelopmentFastAPILangchainMCP
aditya
PROFILE
Aditya
Adi Addepalli developed a new Knowledge Base Client for the awslabs/mcp repository, integrating Amazon Bedrock Knowledge Bases using the Model Context Protocol. He designed an end-to-end sample architecture featuring a Streamlit chat interface as the frontend and a FastAPI backend, enabling users to query knowledge bases through MCP-based endpoints. Adi provided project scaffolding, dependency management, and API documentation to streamline onboarding and internal demos. His work focused on Python, API development, and backend integration, resulting in a scalable pattern for future knowledge-base and chat-based retrieval projects. The solution stabilized demo flows and accelerated adoption without major bug reports.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
2,460
Activity Months1
Your Network
113 people
Work History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 — Delivered a New Knowledge Base Client with Bedrock MCP integration and a Streamlit chat UI for awslabs/mcp. The end-to-end sample includes a Streamlit frontend, a FastAPI backend, and MCP-based endpoints to query knowledge bases, along with project scaffolding and dependencies for quick onboarding and demos. Major bugs were not reported; minor integration tweaks were completed to stabilize the demo flow. Overall, this work provides an immediately usable KB client, accelerating internal demos and adoption, and establishes a scalable pattern for future knowledge-base integrations and chat-based retrieval. Technologies/skills demonstrated include MCP Model Context Protocol, Bedrock Knowledge Bases, Streamlit, FastAPI, Python packaging, API design, and end-to-end sample architecture.
1 Commits • 1 Features
Apr 1, 2025April 2025 — Delivered a New Knowledge Base Client with Bedrock MCP integration and a Streamlit chat UI for awslabs/mcp. The end-to-end sample includes a Streamlit frontend, a FastAPI backend, and MCP-based endpoints to query knowledge bases, along with project scaffolding and dependencies for quick onboarding and demos. Major bugs were not reported; minor integration tweaks were completed to stabilize the demo flow. Overall, this work provides an immediately usable KB client, accelerating internal demos and adoption, and establishes a scalable pattern for future knowledge-base integrations and chat-based retrieval. Technologies/skills demonstrated include MCP Model Context Protocol, Bedrock Knowledge Bases, Streamlit, FastAPI, Python packaging, API design, and end-to-end sample architecture.
April 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API DevelopmentAWS BedrockBackend DevelopmentFastAPILangchainMCPPythonStreamlit
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