Open Source RoboSystems

Build powerful financial analysis tools with SEC filings, graph databases, and AI integration. Deploy locally or to AWS with complete infrastructure automation.

Get Started with RoboSystems

Clone the repository and run the complete stack locally or deploy to AWS

Quick Start - Docker Development Environment

Complete stack with all services configured

The recommended way to run RoboSystems. Includes PostgreSQL with automatic migrations, graph database, Valkey message broker, and all development services pre-configured.

# Clone the repository
git clone https://github.com/RoboFinSystems/robosystems.git
cd robosystems

# Install uv (Python package and version manager)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install just (command runner)
uv tool install rust-just

# Start all services via Docker Compose
just start

# Services available at:
# API: http://localhost:8000
# Docs: http://localhost:8000/docs

Powerful Use Cases

From SEC financial analysis to AI-powered insights, build sophisticated financial applications with RoboSystems

SEC XBRL Pipeline

Load and query financial filings locally

Load company financial filings (10-K, 10-Q) by ticker symbol into a local graph database. Query revenue, net income, assets, and other GAAP metrics across multiple years with Cypher queries.

What You Can Do:

✓Download and process SEC filings for any public company
✓Query financial metrics using Cypher graph database language
✓Integrate with Claude Desktop or Claude Code via MCP
✓Access programmatically via Python or TypeScript clients
✓Compare financials across companies and time periods

Quick Start - Load NVIDIA Filings:

# Start RoboSystems services
just start

# Create a test account with SEC access
just demo-sec

# Load NVIDIA filings (all available years)
just sec-load MSFT

# Query revenue data
just graph-query sec "MATCH (e:Entity)-[:ENTITY_HAS_REPORT]->(r:Report) RETURN r LIMIT 5"

View Full SEC Pipeline Documentation →

AI Integration via MCP

Connect Claude Desktop, Claude Code, or any MCP client

Use the Model Context Protocol (MCP) to give AI assistants direct access to your financial data. Ask questions in natural language and let Claude query your knowledge graph automatically.

Integration Options:

✓Claude Desktop:Add to your config for conversational financial analysis
✓Claude Code:Query financial data while coding and building applications
✓Custom MCP Clients:Build your own AI-powered financial tools

Claude Desktop Configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "robosystems": {
      "command": "npx",
      "args": ["-y", "@robosystems/mcp"],
      "env": {
        "ROBOSYSTEMS_API_URL": "http://localhost:8000",
        "ROBOSYSTEMS_API_KEY": "rfs_your_api_key_here",
        "ROBOSYSTEMS_GRAPH_ID": "sec"
      }
    }
  }
}

Example Questions You Can Ask Claude:

•"What was Apple's revenue for the last 5 years?"
•"Compare NVIDIA and AMD net income trends"
•"Show me Tesla's total assets by quarter"
•"What are the most recent earnings per share for Microsoft?"

Client Libraries & SDKs

Install RoboSystems client libraries for your preferred programming language

TypeScript / JavaScript

Official TypeScript client with React components and hooks.

npm install @robosystems/client

npm →GitHub →

Python

Python client library with Jupyter notebook support.

pip install robosystems-client

PyPI →GitHub →

MCP Client

Model Context Protocol client for AI agent integration.

npx -y @robosystems/mcp

npm →GitHub →

Optional: Production Deployment

Deploy to AWS

Ready for production? GitHub Actions and CloudFormation templates provide complete AWS infrastructure automation

AWS CloudFormation

Infrastructure as Code Templates

Complete AWS infrastructure defined as code. Deploy a production-ready environment with auto-scaling, load balancing, and managed services in minutes.

Included Resources:

✓ECS Fargate API with ALB
✓EC2 hosted graph database clusters with auto-scaling
✓EC2 auto-scaling group for Dagster run workers
✓RDS (Aurora) PostgreSQL with multi-AZ deployment
✓ElastiCache Valkey for caching
✓S3 buckets for data lake and backup storage
✓DynamoDB for instance/graph/volume registry
✓Lambda functions for management and monitoring
✓CloudWatch, Prometheus, and Grafana observability
✓VPC, CloudTrail, Route 53 DNS, and VPC Flow Logs
✓WAF for API protection
✓Secrets Manager for credential management

View CloudFormation Templates →

GitHub Actions CI/CD

Automated Deployment Pipelines

CI/CD pipeline that orchestrates CloudFormation stacks for deployments. The production workflow automatically deploys your entire infrastructure stack to AWS.

Integrated Deployment Pipeline:

✓CloudFormation stack deployment workflows for infrastructure
✓Production and staging environments deployments
✓Release management workflow for automated versioning, changelog generation, and release deployment
✓AI-assisted feature development workflow of PR reviews
✓GitHub Action deployment status monitoring
✓GitHub-hosted runners (free for public repos)
✓Test suite validation before infrastructure deployment
✓Docker image building and ECR push
✓Lambda function packaging and deployment

View GitHub Actions Workflows →

Deploy Your Own RoboSystems in Minutes

Fork our repository and have your own production environment running on AWS within the hour. Add custom data sources in the custom_* namespace and pull upstream updates without merge conflicts.

Fork Repository

Click "Fork" on GitHub to create your own fork of the RoboSystems repository

Configure AWS

Add your AWS and GitHub credentials as GHA Secrets and Variables for automated infrastructure deployment

Deploy Infrastructure

Trigger the production workflow and watch the CloudFormation stacks deploy automatically

Fork on GitHub

Ready to Create Your Own Financial Knowledge Graph?

Get started building your own financial knowledge graph today with our open source platform - on your laptop or in the cloud.

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