Enables blockchain-based dataset trading through Ethereum smart contracts and NFT-based access controls, with automatic purchase handling for dataset access
Provides decentralized data storage and retrieval capabilities for datasets, supporting both public data previews and private encrypted data access
Implements decentralized encryption and access control for private datasets using Lit Protocol's encryption infrastructure
Filecoin Data Broker MCP Server
A Model Context Protocol (MCP) server implementation that provides blockchain-based dataset trading functionality using Filecoin, IPFS, Ethereum smart contracts, and Lit Protocol for decentralized encryption.
Overview
This project implements an MCP server that enables AI agents and applications to discover, purchase, and query datasets stored on Filecoin/IPFS with Ethereum NFT-based access controls. The server provides a secure, decentralized marketplace for data trading with Lit Protocol encrypted private datasets and public dataset previews.
Features
Core Functionality
- Blockchain-Based Dataset Trading: Purchase dataset access through Ethereum NFT contracts
- Lit Protocol Integration: Decentralized encryption and access control for private datasets
- SynapseStorage Integration: Enhanced data fetching and management capabilities
- Automatic Purchase Flow: Seamless NFT purchase during dataset queries
- Public Data Previews: Query public columns without purchase
- SQL Query Interface: Standard SQL queries on purchased datasets
- IPFS/Filecoin Storage: Decentralized data storage and retrieval
MCP Tools
list_datasets
: Lists available datasets with metadata, pricing, and column informationquery_dataset
: Executes SQL queries on datasets with automatic purchase handling
Dataset Types
- Public Columns: Available for querying without purchase, stored on IPFS
- Private Columns: Encrypted with Lit Protocol, require NFT ownership to decrypt and access
- Hybrid Access: Full dataset access includes both public and private data after purchase
Architecture
Core Components
- Entry Point:
bin/index.js
- MCP server startup with stdio transport - Server:
server.js
- MCP server instance and tool registration - Dataset Factory:
lib/dataset/factory.js
- Abstract dataset creation and management - Blockchain Integration:
lib/contracts/FDBRegistry.js
- Ethereum contract interactions - Encryption Layer:
lib/lit.js
- Lit Protocol integration for decentralized encryption - Storage Layer:
lib/synapse.js
- SynapseStorage for enhanced data operations
Dataset Implementations
- FilecoinDataset:
lib/dataset/filecoin/FilecoinDataset.js
- Production blockchain-based datasets with Lit Protocol decryption - LocalDataset:
lib/dataset/mock/LocalDataset.js
- Development/testing mock datasets
Security & Data Processing
- SQL Security:
lib/sql.js
- Query sanitization and access control - Ethereum Integration:
lib/signer.js
- Blockchain authentication and wallet management - Decentralized Encryption: Lit Protocol for secure data access control
Setup
Prerequisites
- Node.js ≥20.0.0 (required for private field syntax)
- Ethereum private key for blockchain access
- Access to Ethereum network (mainnet or testnet)
Installation
Manual Execution
Claude Desktop
Development Mode
- Edit
.env
file by filling required values - Start MCP inspector and auto-reload:
This provides a debugging interface for testing tool calls and responses.
Usage
Basic Workflow
- List Available Datasets:
- Use
list_datasets
tool to see available datasets - Review metadata, pricing, and column information
- Public columns are immediately queryable
- Use
- Query Datasets with Automatic Purchase:
- Use
query_dataset
tool with SQL queries - System automatically handles NFT purchase for private data access
- Payment processed through Ethereum smart contract when needed
- Lit Protocol handles decryption of private datasets post-purchase
- Use
Example Tool Usage
List datasets:
Query dataset:
Project Structure
Development
Coding Conventions
- Module System: ESM modules with
.js
extensions in imports - Private Fields: Modern
#fieldName
syntax for encapsulation - Async Patterns: Prefer async/await over Promise chains
- Type Safety: JSDoc comments with TypeScript syntax for type hints
Testing with Local Datasets
For development without blockchain dependency:
- Switch to
LocalDatasetFactory
inlib/dataset/factory.js
- Use sample data from
sample/
directory - Test tool functionality with MCP inspector
Adding New Tools
- Create tool file in
lib/tools/
directory - Follow existing tool patterns with Zod schemas
- Import and register in
server.js
- Test with
npm run dev
and MCP inspector
Blockchain Development
- Test on testnet before mainnet deployment
- Use environment variables for network configuration
- Handle gas costs and transaction failures gracefully
- Implement proper error handling for network issues
Security Considerations
Access Control
- NFT ownership verification for private dataset access
- SQL query sanitization to prevent injection attacks
- Ethereum private key protection via environment variables
Data Privacy
- Public columns available for preview without purchase
- Lit Protocol provides decentralized encryption and access control
- Automatic purchase and decryption workflows for seamless data access
Query Security
- Row limits enforced on SQL queries
- Table name restrictions and input validation
- Error messages that don't leak sensitive information
License
MIT
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Enables AI agents to discover, purchase, and query blockchain-based datasets using Filecoin/IPFS storage with Ethereum NFT access controls and Lit Protocol encryption. Provides a decentralized marketplace for secure dataset trading with automatic purchase workflows and SQL query capabilities.
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