Databento™ MCP

Model Context Protocol server for Databento™ market data

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Installation

pip install databento-mcp

Quick Start

1. Get your API key from Databento
2. Configure your MCP client (see setup guides below)
3. Start querying market data through your AI assistant

Setup Guides

Claude Desktop

Add to your configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "databento": {
      "command": "databento-mcp",
      "env": {
        "DATABENTO_API_KEY": "your-api-key"
      }
    }
  }
}

GitHub Copilot CLI

Add the server to your Copilot CLI configuration:

gh copilot config set mcp-servers '{
  "databento": {
    "command": "databento-mcp",
    "env": {
      "DATABENTO_API_KEY": "your-api-key"
    }
  }
}'

Or add to your ~/.config/gh-copilot/config.yml:

mcp-servers:
  databento:
    command: databento-mcp
    env:
      DATABENTO_API_KEY: your-api-key

See GitHub Copilot CLI MCP documentation for more details.

ChatGPT (via Developer Mode)

ChatGPT supports MCP servers through Developer Mode.

1. Enable Developer Mode in ChatGPT settings
2. Add an MCP server with the following configuration:

{
  "name": "databento",
  "command": "databento-mcp",
  "env": {
    "DATABENTO_API_KEY": "your-api-key"
  }
}

See OpenAI Developer Mode documentation for detailed setup instructions.

Features

Historical Data

• Retrieve trades, OHLCV bars, market depth, and more
• Support for all Databento schemas (trades, mbp-1, mbp-10, ohlcv-*, etc.)
• Cost estimation before query execution
• Smart data summaries with statistics

Live Data

• Real-time market data streaming
• Configurable stream duration
• Multiple schema support

File Operations

• Read/write DBN format files
• Export to Apache Parquet
• Convert between formats

Batch Processing

• Submit large-scale batch jobs
• Monitor job status
• Download completed files

Reference Data

• Symbol metadata and definitions
• Symbology resolution
• Dataset discovery
• Publisher information

Quality & Performance

• Smart caching with configurable TTL
• Data quality analysis
• Connection pooling
• Comprehensive metrics

Available Tools

Tool	Description
health_check	Check API connectivity and server status
get_historical_data	Retrieve historical market data
get_live_data	Stream real-time market data
get_cost	Estimate query cost before execution
get_symbol_metadata	Get instrument definitions and mappings
search_instruments	Search for symbols with wildcards
list_datasets	List available Databento datasets
list_schemas	List available data schemas
resolve_symbols	Convert between symbology types
submit_batch_job	Submit batch data download
list_batch_jobs	List batch job status
get_batch_job_files	Get batch job download info
cancel_batch_job	Cancel pending batch job
download_batch_files	Download completed batch files
read_dbn_file	Parse and read DBN files
get_dbn_metadata	Get DBN file metadata
write_dbn_file	Write data to DBN format
convert_dbn_to_parquet	Convert DBN to Parquet
export_to_parquet	Query and export to Parquet
read_parquet_file	Read Parquet files
get_session_info	Get trading session info
list_publishers	List data publishers
list_fields	List schema fields
get_dataset_range	Get dataset date range
list_unit_prices	Get pricing information
analyze_data_quality	Analyze data quality issues
quick_analysis	Comprehensive symbol analysis
get_account_status	Server status and metrics
get_metrics	Performance metrics
clear_cache	Clear API response cache

Configuration

Environment Variable	Description	Default
DATABENTO_API_KEY	Databento API key (required)	-
DATABENTO_DATA_DIR	Restrict file operations to directory	Current directory
DATABENTO_LOG_LEVEL	Logging level (DEBUG, INFO, WARNING, ERROR)	INFO
DATABENTO_METRICS_ENABLED	Enable metrics collection	true

Common Datasets

Dataset	Description
GLBX.MDP3	CME Globex (ES, NQ, CL futures)
XNAS.ITCH	Nasdaq TotalView
XNYS.PILLAR	NYSE
DBEQ.BASIC	Consolidated US equities
OPRA.PILLAR	US options
IFEU.IMPACT	ICE Futures Europe

Common Schemas

Schema	Description
trades	Individual trades
ohlcv-1m	1-minute OHLCV bars
ohlcv-1h	1-hour OHLCV bars
ohlcv-1d	Daily OHLCV bars
mbp-1	Top of book
mbp-10	10-level order book
tbbo	Top bid/offer
definition	Instrument definitions

Development

# Clone repository
git clone https://github.com/deepentropy/databento-mcp.git
cd databento-mcp

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src/
ruff check src/

License

MIT License

Links

• Databento Documentation
• Databento Python SDK
• MCP Specification