Flat Files S3 API

Bulk Historical Market Data

Access large-scale historical market datasets through an S3-compatible API, native Snowflake integration, and a hosted Model Context Protocol (MCP) server. Retrieve years of historical data efficiently without paginating API requests or managing custom export pipelines.

The FinFeedAPI Flat Files API is built for quantitative research, AI model training, financial analytics, backtesting, and large-scale data engineering. Historical datasets are organized into predictable file structures, making it easy to browse, download, process, and integrate market data into analytical workflows and cloud data platforms.

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Historical Market DataBulk Datasets

3Data Access Methods

S3 CompatibleExisting Tools & SDKs

AI ReadyHosted MCP Server

What Data Will You Get?

Historical OHLCV Market Data

Access historical OHLCV (Open, High, Low, Close, Volume) datasets. Data is pre-aggregated and ready for analysis.

Daily T+1 Data Snapshots

All OHLCV datasets are delivered on a T+1 daily basis. Each file represents a completed and validated trading period.

Bulk Historical Coverage

Flat Files provide bulk access to historical OHLCV data. This is intended for large-scale research and backtesting workflows.

CSV File Format

All datasets are delivered as CSV files. This allows easy loading into databases, data warehouses, and analytics tools.

S3-Compatible Data Access

Files are distributed via an S3-compatible API. Standard object storage clients can be used for authentication and downloads.

Time-Series Structured Data

OHLCV files are structured as time-series data, ordered by time. No additional aggregation is required before use.

Consistent File Schema

Each dataset follows a stable and consistent schema across delivery dates. This reduces maintenance effort in downstream data pipelines.

Partitioned by exchange, period and data date

Files are organized by delivery date, enabling selective downloads. This helps limit data transfer to only the required periods.

Optimized for Offline Processing

Flat Files are designed for offline and batch processing, not real-time access. They fit machine learning, historical modeling, and analytical workloads.

Data for Archive and Research

T+1 OHLCV Flat Files support long-term storage and reproducibility. This makes them suitable for audits, research replication, and compliance use cases.

Unique Capability

Historical Market Data Built for Scale

Most market data APIs are designed to answer individual queries. The Flat Files API is designed to move entire datasets.

Instead of making millions of API requests to retrieve years of historical data, applications can download compressed datasets organized by exchange, timeframe, and date through a predictable directory structure compatible with existing S3 tools and cloud workflows.

The result is significantly simpler infrastructure for quantitative research, large-scale backtesting, AI training, financial analytics, and historical data warehousing.

Whether you process data with Python, Spark, Snowflake, SQL, or custom analytics pipelines, the Flat Files API delivers historical market data in formats built for bulk processing rather than interactive querying.

AI Applications

Built for AI Applications with MCP

The Flat Files API includes a hosted Model Context Protocol (MCP) server that allows AI assistants and autonomous applications to discover available datasets before downloading them. Rather than hardcoding bucket names or file paths, AI applications can browse available storage buckets, exchange prefixes, dataset families, and individual objects through self-describing MCP tools. Once the required dataset has been identified, the corresponding file can be retrieved through the standard S3-compatible API.

Flat Files MCP

json

{
  "mcpServers": {
    "FinFeedAPI-Flat-Files": {
      "url": "https://mcp.flatfiles.finfeedapi.com/mcp",
      "headers": {
        "X-APIKey": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Hosted MCP server maintained by FinFeedAPI
Self-describing storage discovery tools (storage_list_buckets, storage_list_objects)
Browse buckets, exchange prefixes, and file keys programmatically
Standard X-APIKey header authentication
Native support for Cursor, Claude Desktop, and custom MCP agent runtimes

Protocols & Interfaces

Multiple Access Methods

Choose the interface that best matches your data engineering and analytics workflow. All interfaces provide access to the same underlying historical datasets while supporting different engineering workflows.

Interface	Best For
S3-Compatible API	Bulk historical data downloads using existing S3 tools and SDKs
Snowflake	Query historical datasets directly from your cloud data warehouse
Hosted MCP Server	AI agents discovering available buckets, datasets, and files before retrieval

Platform Specifications

Engineering Standards

Built for reliable, high-volume historical data processing.

Predictable File Organization

Exchange, dataset type, timeframe, and date-based hierarchy for automated ingestion.

Gzip-compressed CSV

Optimal balance between compression ratio, readability, and parsing speed.

S3 Compatibility

Works seamlessly with AWS CLI, S3 Browser, Boto3, and standard S3 SDKs using X-APIKey / AWS SigV4 auth.

Cloud Analytics Ready

Direct Snowflake querying for instant SQL analytical access.

Pre-Download File Metadata

Inspect key names, last modified timestamps, and file sizes before triggering downloads.

Competitive Advantage

FinFeedAPI vs Traditional Historical Data Delivery

Retrieving years of historical market data through traditional APIs often requires millions of requests, pagination, custom export jobs, and significant engineering effort. The Flat Files API is designed specifically for large-scale historical data distribution.

Feature	Traditional APIs	FinFeedAPI Flat Files API
Large Historical Datasets	Millions of paginated requests	Bulk downloadable datasets
Data Organization	Request-driven retrieval	Structured Exchange, Timeframe, and Date hierarchy
Bulk Processing	Requires custom pagination & export logic	Ready-to-process flat files (.csv.gz)
Storage Compatibility	Proprietary REST endpoints	Standard S3-compatible REST API
Dataset Discovery	Static documentation searching	Hosted MCP programmatic discovery
File Format	Verbose JSON responses	Semicolon-delimited compressed CSV

Onboarding

Quickstart

Start working with historical market datasets in just a few minutes.

1Create your free FinFeedAPI account.
2Generate an API key.
3Browse available datasets using MCP or the S3 API.
4Locate the required exchange and dataset prefix.
5Download historical files through the S3-compatible interface or query data from Snowflake.

The documentation includes S3 authentication, supported tools, dataset layouts, naming conventions, and implementation examples.

Example

List available objects inside a dataset prefix:

bash

curl -X GET \
  -H "Accept: application/xml" \
  -H "Authorization: YOUR_API_KEY" \
  "https://s3.flatfiles.finfeedapi.com/finfeedapi/?prefix=E-IEXG/T-OHLCV+TP-1DAY/"

The response returns XML-formatted object listings with full keys, modification timestamps, and exact file sizes.

The Challenge

Historical Data Doesn't Scale Well Through REST APIs

Historical market datasets continue to grow every trading day.

Downloading months or years of data through traditional REST APIs often means handling pagination, retry logic, rate limits, and millions of individual requests before analysis can even begin.

Bulk datasets eliminate this overhead.

Structured Files, Familiar Tools

The Flat Files API organizes historical market data into structured files that can be downloaded efficiently, processed in parallel, stored in cloud data warehouses, and integrated into existing analytics infrastructure using familiar S3-compatible tools.

Instead of optimizing API calls, engineering teams can focus on analyzing data.

Use Cases

Common Applications

Quantitative research
Historical backtesting
AI and machine learning training
Financial data warehouses
Cloud analytics platforms
Snowflake data pipelines
Market surveillance
Long-term trend analysis
Historical OHLCV analysis
Large-scale market data archiving

Start Building

Access historical market datasets through one scalable platform built for bulk data retrieval, cloud analytics, and AI workflows.

If you're training machine learning models, building quantitative research pipelines, maintaining historical data warehouses, or analyzing years of market activity, the FinFeedAPI Flat Files API provides an efficient way to retrieve and process historical market data at scale.