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SkillsMay 13, 2026·3 min de lecture

MiroFish — Universal Swarm Intelligence Prediction Engine

An open-source swarm intelligence engine that uses multi-agent simulation and knowledge graphs to predict trends in social, financial, and public opinion domains.

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Native · 98/100Policy : autoriser
Surface agent
Tout agent MCP/CLI
Type
Skill
Installation
Single
Confiance
Confiance : Established
Point d'entrée
MiroFish Overview
Commande CLI universelle
npx tokrepo install 7368bde3-4f09-11f1-9bc6-00163e2b0d79

Introduction

MiroFish is an open-source swarm intelligence engine that coordinates multiple LLM agents to analyze data, build knowledge graphs, and generate predictions. It applies multi-agent simulation to domains like financial forecasting, public opinion analysis, and trend prediction.

What MiroFish Does

  • Coordinates swarms of specialized agents to collaboratively analyze complex datasets
  • Builds and queries knowledge graphs to surface relationships in unstructured data
  • Generates predictions for financial markets, social trends, and public opinion shifts
  • Provides structured reports with confidence scores and supporting evidence
  • Supports custom prediction tasks defined through natural language prompts

Architecture Overview

MiroFish uses a multi-agent architecture where specialized agents (data collector, analyst, predictor, critic) communicate through a shared knowledge graph. The orchestration layer distributes tasks, aggregates agent outputs using swarm consensus algorithms, and produces a final prediction with a confidence interval. The system uses LLM backends for reasoning and Python for data processing.

Self-Hosting & Configuration

  • Install via pip with Python 3.9+ and configure LLM API keys in environment variables
  • Supports OpenAI, Anthropic, and local model backends through a unified adapter
  • Knowledge graph storage defaults to a local SQLite database; PostgreSQL optional for scale
  • Custom data connectors can be added for proprietary data sources
  • GPU not required for inference; training custom agents is optional

Key Features

  • Swarm consensus mechanism aggregates diverse agent perspectives into robust predictions
  • Dynamic knowledge graph construction from unstructured text and structured data
  • Multi-domain support covering finance, social media, public policy, and technology trends
  • Confidence scoring with explainable reasoning chains for each prediction
  • Agent memory enables learning from past prediction accuracy across sessions

Comparison with Similar Tools

  • TradingAgents — focused on financial trading; MiroFish handles broader prediction domains
  • CrewAI — general multi-agent orchestration; MiroFish adds swarm consensus and knowledge graphs
  • AutoGen — multi-agent conversations; MiroFish specializes in structured prediction workflows
  • LangGraph — agent graph framework; MiroFish provides a complete prediction application on top

FAQ

Q: What types of predictions can MiroFish make? A: Financial trends, social media sentiment shifts, technology adoption curves, and custom domains.

Q: Does it require real-time data feeds? A: No. MiroFish works with both historical datasets and real-time data connectors.

Q: How does swarm consensus differ from a single agent? A: Multiple agents analyze independently, then consensus algorithms weight and merge their outputs for higher accuracy.

Q: Can I add custom agent types? A: Yes. The plugin system supports custom agent roles with specialized prompts and tools.

Sources

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