AWS Lambda Powertools Documentation Search

AWS Documentation

Access valuable AWS documentation, conduct efficient content searches, and receive personalized recommendations with the Model Context Protocol (MCP).

AWS Labs

Enhance your enterprise workflows and optimize cost analysis with seamless integration into various AWS services such as Bedrock Knowledge Bases, Nova Canvas, Step Functions, Lambda, IAM, and Cost Explorer. This Model Context Protocol (MCP) facilitates infrastructure management and empowers generative AI applications through dedicated servers, complete with sample implementations and deployment assistance.

Documentation Search

Gain immediate access to comprehensive technical documentation covering over 40 top frameworks and libraries such as Python, React, FastAPI, and AWS. Benefit from smart caching and streamlined retrieval to enhance your development processes.

Documentation Search

Discover the latest content from well-known documentation platforms like LangChain, LlamaIndex, and OpenAI with seamless Google search integration and advanced content retrieval capabilities.

Open Docs (Technical Documentation Search)

Discover and catalog technical document repositories featuring multilingual support by utilizing jieba-wasm alongside Lunr.js for comprehensive full-text search functionalities.

MkDocs Search

Unlock the ability for artificial intelligence (AI) systems to effortlessly explore and fetch data from MkDocs documentation platforms. This is achieved by utilizing established Lunr.js indices and transforming HTML into markdown format, ensuring a smooth and streamlined integration process.

Technical Documentation Search

Unlock a specialized search tool within the Model Context Protocol (MCP) ecosystem, enabling AI assistants to seamlessly retrieve and utilize technical insights from LangChain, LlamaIndex, and OpenAI repositories. This innovative tool harnesses the power of the Brave Search API to efficiently locate, retrieve, and extract pertinent information, enhancing the overall AI experience.

Rust Documentation

Discover a comprehensive resource hub for AI applications, offering easily accessible Rust documentation, coding templates, and troubleshooting answers. Accessible via a TypeScript server, this platform aggregates and organizes content from docs.rs, GitHub, and various community outlets.

Python Documentation Search

Empower AI virtual assistants to access current information from well-known Python libraries by conducting precise searches on Google within defined documentation areas to extract pertinent details.

JavaScript WebAssembly Tools

Unlock the potential of WebAssembly technology with a versatile server component that simplifies tasks such as echo functionality, knowledge graph queries, and handling HTTP requests. Seamlessly integrate this component into WebAssembly-compatible environments using a user-friendly SDK to develop tailored tools.

AWS Resources

Unlock the capabilities of querying AWS services such as S3 and CodePipeline with the Model Context Protocol (MCP). This interface, developed in Python, empowers seamless execution of DevOps activities and efficient cloud resource administration.

Perplexity AI Search

Enhance your web search experience by seamlessly connecting with Perplexity AI's cutting-edge search functions, allowing for advanced AI-driven search queries through the utilization of TypeScript and the OpenAI SDK.

AWS Lambda

Facilitates communication between LLMs and AWS Lambda functions, allowing connectivity to restricted assets, AWS features, and leveraging Lambda’s data handling and integration with external APIs.

AI Meta Tool Creator

Empower artificial intelligence systems to efficiently generate, run, and oversee personalized utilities within a protected sandbox setting, supporting JavaScript, Python, or shell scripting along with persistent data storage functions.

Technical Documentation Search

Enhance your AI assistants by linking them with essential technical resources like LangChain, LlamaIndex, and OpenAI using specialized search techniques and content retrieval methods.