MIRA
Molecule Insights & Research Assistant
Overview
MIRA serves as the connective layer between complex scientific research and the growing community participating in decentralized science. It combines a curated knowledge base, real-time market data via Model Context Protocol (MCP), and AI-powered project scoring to serve researchers, traders, and institutions. The name—Molecule Insights & Research Assistant—reflects its dual purpose: delivering deep insights while guiding users through the complexities of IP-NFTs, IPTs, and decentralized funding.
MIRA serves three core user groups:
Researchers — Understanding DeSci, structuring IP, navigating the minting process
Traders/Investors — Accessing real-time token data, project insights, and market intelligence
DAOs & Institutions — Evaluating project maturity through standardized scoring frameworks
Key Capabilities
Scoped Expertise: Answers queries specifically about Molecule's products, IP-NFTs, IPTs, decentralized science (DeSci), bioDAOs, and funding mechanisms using curated local sources and real-time API data.
Real-Time Market Intelligence: Retrieves live token prices, holder distributions, liquidity metrics, project activity, and historical price data through MCP tools connected to Molecule's APIs.
AI-Powered Project Scoring: Analyzes Data Room files to generate Technology Readiness Level (TRL) assessments and weighted evaluation scores covering therapeutic relevance, optionality, and IP strength.
Context Awareness: Detects the user's current page and viewing context, tailoring responses to the specific token or project being explored.
Safe and Transparent: Employs responsible AI design—it knows when to say "I don't know" and defers to human experts to avoid misinformation. Never provides investment advice.
Source Attribution: Every response links back to its origin, ensuring traceability and accountability. Performance and feedback are tracked via Langfuse to continually improve response quality.
Web Search Fallback: If local knowledge is insufficient but relevant, MIRA augments its answers by retrieving current information from trusted online sources.
Architecture & Workflow
User Query
Extract Context (current token/page being viewed)
Search Local Knowledge (LanceDB)
If sufficient → answer directly
If real-time data needed → execute MCP tools
If insufficient but relevant → perform web search
If off-topic → politely decline
Generate Response with linked sources
User Feedback & Tracking via Langfuse
Tech Stack:
OpenAI GPT-4o
Powers reasoning, tool selection, and response generation
Model Context Protocol
Connects to Molecule APIs for real-time token and project data
LanceDB
Vector-based semantic search for curated documentation
Vercel AI SDK
Streaming responses and tool orchestration
Upstash Redis
Caching layer for API responses
Sanity CMS
Stores and manages AI-generated project scores
Langfuse
Monitors performance metrics and feedback
Tavily API
Web search for current information beyond local knowledge
molecule-get-ipts
Token listings with market data, holders, and liquidity
molecule-get-project-activity
Announcements, file updates, and data room changes
molecule-get-ipt-categories
Research categories and associated assets
molecule-get-project-summary
Comprehensive overviews with price history
molecule-get-ipt-historic-prices
Daily OHLCV data up to 90 days
Evolution & Strategy
v0 — Knowledge Foundation: Launched as Molecule's first AI-driven tool, MIRA v0 established a context-aware assistant built on curated knowledge from official documentation, protocol blogs, and DeSci standards. It responds only from verified sources, preventing hallucination and ensuring reliability.
v1 — Real-Time Integration: Introduced MCP tool integration for live market data and was embedded directly into the Molecule Screener. Added context awareness to understand which token users are viewing, enabling natural conversational flows with quick actions for common queries.
v2 — Project Scoring (Current): Expanded to analyze Data Room contents and generate standardized project assessments. Scores flow through a review pipeline—from AI generation through human validation to publication via Sanity CMS—ensuring appropriate oversight.
v3 — Knowledge Graphs (Planned): Future iterations will introduce relationship mapping across the ecosystem, connecting projects, researchers, and institutions through interactive visualizations. This phase also addresses confidential data handling and explores token-gated access models.
Check our MIRA Github Repo for more info.
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