Agents forget everything after each task!Graphiti builds a temporal knowledge graph for Agents that provides a memory layer to all interactions.Fully open-source with 20k+ stars!Learn how to use Graphiti MCP to connect all AI apps via a common memory layer (100% local): https://t.co/cpAZFJcrufAvi Chawla (@_avichawla):Big update for Claude Desktop and Cursor users!Now you can connect all AI apps via a common memory layer in a minute.I used the Graphiti MCP server that runs 100% locally to cross-operate acros ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. https://t.co/Op1RqVm3agAvi Chawla (@_avichawla):Big update for Claude Desktop and Cursor users!Now you can connect all AI apps via a common memory layer in a minute.I used the Graphiti MCP server that runs 100% locally to cross-operate across AI apps like Claude Desktop and Cursor without losing context.(setup below) https://t.co/AZrxcS2cR5 ...

Graphiti GitHub repo: https://t.co/knIZDLAxPg(don't forget to star it ⭐) ...

1) Docker SetupDeploy the Graphiti MCP server using Docker Compose.This setup starts the MCP server with Server-Sent Events (SSE) transport, and it includes a Neo4j container, which launches the database as a local instance.This configuration also lets you query and visualize the knowledge graph using the Neo4j browser preview.You can also use FalkorDB.2) Connect MCP server to CursorWith tools and our server ready, let's integrate it with our Cursor IDE!Go to: File → Preferences → Cursor Settings → MCP → Ad ...

Big update for Claude Desktop and Cursor users!Now you can connect all AI apps via a common memory layer in a minute.I used the Graphiti MCP server that runs 100% locally to cross-operate across AI apps like Claude Desktop and Cursor without losing context.(setup below) https://t.co/AZrxcS2cR5 ...

RT Avi Chawla (@_avichawla)You can now deploy any ML model, RAG, or Agent as an MCP server.And it takes just 10 lines of code.Here's a breakdown, with code (100% private): ...

LitServe GitHub repo: https://t.co/nMAIk0yBGI(don't forget to star it 🌟) ...

Connecting AI models to different apps usually means writing custom code for each one.For instance, if you want to use a model in a Slack bot or in a dashboard, you'd typically need to write separate integration code for each app.Let's learn how to simplify this via MCPs.We’ll use @LightningAI's LitServe, a popular open-source serving engine for AI models built on FastAPI.It integrates MCP via a dedicated /mcp endpoint.This means that any AI model, RAG, or agent can be deployed as an MCP server, accessible ...

You can now deploy any ML model, RAG, or Agent as an MCP server.And it takes just 10 lines of code.Here's a breakdown, with code (100% private): ...

RT Avi Chawla (@_avichawla)Image scraping is finally here!Firecrawl’s latest v2 endpoint now lets you scrape visual content from the web to build multimodal LLM apps, fine-tune LLMs, and more.You can also apply specific filters like resolutions, aspect ratios, or image types.66k+ stars on GitHub! https://t.co/6uXa9am9ri ...