The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
PARIKSHA AI is an intelligent newsroom assistant that automates the process of fact verification.
It:
Extracts key claims from articles
Verifies them using real-time web sources
Assigns a credibility score
Detects bias and weak sources
Maintains an audit log of all verifications
It has won many awards in tech-events.
Try Pariksha - https://jhizrpnvqubw9rmh5r7yod.streamlit.app/
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Snow White went into business. I built her a website.
Merry Lantern Ledger is my side project: a team of AI agents investigating business ideas in public. Each idea earns its next step through evidence, with a record of what the team tried and learned.
I built it with AI tools, bringing illustration, motion and product design into the same little fairytale world. The cast breathes, the beards sway, and the serious work has somewhere to live.
AI enhances exploration and scaffolding; tactics, strategy, direction and taste stay under my thumb.
A little scroll through the world so far.
Feel free to check it out.
https://merrylanternledger.com
InteractPro- Realtime Collaboration & AI Chat Platform
Live link: https://interactpro.vercel.app/
Github link: https://github.com/nitinjha7/InteractPro-ChatApplication
React, TypeScript, Node.js, Express, tRPC, PostgreSQL, Prisma, Socket.IO, Yjs, Gemini, pgvector
A developer-focused platform combining real-time messaging, collaborative code editing, persistent sessions, and AI-powered semantic search over private conversations.
Key features
1) Real-time one-to-one chat and syntax-highlighted code sharing.
2) Concurrent collaborative editing using Yjs CRDTs and WebSockets.
3) Persistent code sessions with database-backed state recovery.
4) RAG-based semantic search using Gemini embeddings, PostgreSQL pgvector and HNSW indexing.
5) Answers grounded in relevant messages with citations.
6) 71 manually written server-side tests.
What was the trickiest part of getting Yjs and the saved sessions to work together? I'm curious how you handled someone reconnecting after others had kept editing.
An open-source MCP (Model Context Protocol) server that lets AI assistants like Claude work with X directly, using 11 tools built on the X API v1 and v2.
Agents can post and search content, look up and update profiles, follow and unfollow accounts, list followers and following, and create and manage public or private lists.
It's set up with environment-based API keys and stdio transport, plus GitHub Actions for publishing and releases. It's part of my open-source MCP series, alongside servers for LinkedIn, Medium, and Kaggle.
You've built MCP servers for a few different platforms now. Have you found any tool names or descriptions that made a noticeable difference in how reliably the agent chose the right tool? I'd be interested to hear what you ended up changing.