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NEW: Prediction Markets API

One REST API for all prediction markets data
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Limitless Historical Market Insights with S3 Flat Files

Supercharge your financial analysis and trading strategies. Get direct, scalable, and seamless access to petabytes of historical stock market data, delivered in a simple, developer-friendly format.
Get a Free API KeySee Pricing
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20+
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Years of market history
50
TB
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Historical market data
7
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Official SDKs
5+
+
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Core data types
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Access Decades of Market Data

FinFeedAPI Flat Files S3 API is your direct, high-speed gateway to a petabyte-scale archive of historical market data. We've eliminated the complexity of bulk data acquisition by using a language your team already knows: the Amazon S3 API. Plug directly into our data repository with your existing tools and scripts, skip the learning curve, and empower your team to focus on what matters: quantitative analysis, ML modeling, and comprehensive backtesting.
Read Docs
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What you get

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Direct S3 API Access
Connect using a powerful and flexible RESTful API compatible with Amazon S3 for seamless integration.
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Rich Historical Datasets
Gain access to essential market data including daily OHLCV (Open, High, Low, Close, Volume), trades, and quotes.
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Simple File Structure
Data is logically organized by exchange, data type, and date, making it easy to locate and retrieve the specific files you need.
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Flexible Authentication
Secure your access with multiple authentication methods, including API keys and AWS Signature Versions 2 and 4
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Broad Tool Compatibility
Works out-of-the-box with popular tools like the AWS CLI and S3 Browser.
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Secure & Standardized Connections
The API supports HTTP/1.0, HTTP/1.1, and HTTP/2.0 standards , with secure HTTPS endpoints strongly recommended for production use.
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Efficient Filtering
Utilize the prefix parameter to easily filter and list only the objects you need, narrowing down results by date or exchange for faster queries.
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Clear Error Handling
Receive standard HTTP status codes and detailed XML error messages consistent with Amazon S3.
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MCP Compability
Plug the API directly into AI applications with almost no effort.

MCP compability for seamless data integration

FinFeedAPI supports the Model Context Protocol (MCP), an open specification that makes our financial data APIs machine-readable. This allows AI models, autonomous agents, and next-generation crypto apps to programmatically discover and integrate our data with little to no custom code.

Key benefits for users include:

  • Easy AI Integration: Directly connect FinFeedAPI data to large language models (LLMs) and AI agents.
  • Simplified Development: Access all FinFeedAPI services through a single, unified MCP endpoint, eliminating the need for custom wrappers.
  • Increased Reliability: Schema-level validation catches errors and ensures more robust integrations.
  • Future-Proof Design: New services and endpoints are automatically discovered by your applications without requiring client-side updates.

Why this is the best choice for developers

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Leverage Familiar Tools
There's no need to learn a new proprietary API. Use the tools you already know and love, including the AWS CLI, Boto3 for Python, and official AWS SDKs for dozens of other languages.
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Simple & Focused API
We've implemented the most critical S3 operations for data retrieval: ListObjects and GetObject. This focused approach makes the API incredibly simple and predictable to work with.
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Optimized for Performance
The API is purpose-built and optimized for listing and downloading large datasets, ensuring you can retrieve terabytes of data quickly and reliably.
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Easy-to-Parse Data
Access the full EDGAR universe: 30+ years of history, 400+ form types, and near real-time updates. Fuel apps with comprehensive historical data and react instantly to market-moving events.
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Comprehensive Examples
Our documentation includes detailed configuration and usage examples for popular S3 clients and SDKs to get you started in minutes
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Transparent, Scalable & Accessible
Get started instantly and scale effortlessly with clear, developer-friendly pricing tiers based on usage. No complex per-seat licenses or opaque enterprise contracts.

Use cases

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Use case: Academic research

Empirical research in finance, economics, and data science depends on access to vast, high-quality historical market data. Researchers face the challenge of sourcing comprehensive, granular, and unbiased datasets that are large enough to test hypotheses, train complex models, and produce statistically significant results.

Learn how we solved that
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Let's Chat!

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