What data is filing-backed versus market-data driven?

Income statements, balance sheets, cash flow statements, ratio and growth views, and SEC filings are grounded in filing-derived records for U.S. listed issuers. Quote and valuation provide the market-data side of the workflow.

Which AI clients support the ApiFinance AI MCP server?

The remote MCP server works with clients that support OAuth and remote MCP, including Claude Desktop, Claude web, Claude Code, Cursor, and custom MCP-compatible agent runtimes.

Is there an official Python SDK?

Yes. ApiFinance AI provides an official Python SDK today, and the investor-grade endpoint family is being aligned around the same security, market, statement, filing, and earnings workflow shown in this documentation.

How far back does historical fundamental coverage go?

ApiFinance AI supports up to 30+ years of financial history where filings are available, allowing long-horizon screening, trend analysis, and model backtesting.

Where can I review data provenance and coverage limits?

Start with the data provenance and data coverage documentation to review supported exchanges, filing-backed source trails, update cadence, and field normalization details before deployment.

Investor-Grade Stock API For Research Tools, AI Agents, and MCP Workflows

Use one structured API for security search, quote data, valuation, statements, SEC filings, insider trading, and earnings-calendar workflows.

Get Free API Key Test In Playground View API Docs

Start with one clear evaluation path

The fastest path is simple: confirm the response shape, inspect source-linked data, then create a key only if the workflow fits.

1. Validate the payload

Run a request before you commit

Use the public playground to inspect JSON shape, endpoint fit, and symbol coverage before you wire the API into a product.

Open playground

2. Check the data trust layer

Review provenance and coverage

Verify what is filing-backed, what the coverage limits are, and where source-linked metadata fits into research or compliance workflows.

Review trust details

3. Move into implementation

Use REST or connect through MCP

Start with direct endpoint calls or connect the MCP server in Claude, Cursor, or another agent runtime once the shape and workflow fit are clear.

View MCP setup

Build finance workflows without stitching together multiple vendors

ApiFinance AI is for teams that need one compact response layer for search, quote and valuation context, statement history, filing evidence, and earnings-event analysis.

Search To Ticker Resolution
Resolve company keywords into supported tickers before you run quote, statement, or filing requests.
Evidence-Ready Workflows
Link statements and earnings analysis back to SEC filings instead of relying on scraped summaries.
Market And Statement Context
Combine quotes, valuation, and CPA-grade statements in one schema family.

Research endpoints built for stock analysis

These endpoints are organized around how disciplined investors actually work: find the ticker, read the market, audit the statements, and trace conclusions back to filings and earnings events.

Discovery

Search

Resolve company keywords into supported tickers before any downstream quote, valuation, statement, or filing request.

querytickercik

View endpoint docs

Market state

Quote

Read current price, volume, change, and trailing return context for a single ticker without extra vendor stitching.

pricevolumereturn_1y

View endpoint docs

Current valuation

Valuation

Inspect market cap, enterprise value, and core multiple fields in a dedicated valuation response.

market_cappe_ratiofcf_yield

View endpoint docs

Statement layer

Income statements

Pull multi-period reported income rows with timeframe, fiscal-year filters, and row limits.

revenueoperating_incomediluted_eps

View endpoint docs

Evidence trail

SEC filings

Filter SEC filing metadata by ticker, date range, form, and accession number for audit-ready workflows.

accession_numberformfiling_date

View endpoint docs

Event layer

Earnings calendar

Inspect earnings-calendar rows with ticker, date, estimate, and surprise context when available.

earning_dateeps_forecasteps_surprise

View endpoint docs

Connect AI Agents with MCP

Use Model Context Protocol (MCP) to let your AI agents access financial data securely. Structured JSON responses, clear endpoint boundaries, and OAuth-ready flows keep the integration predictable and compact for LLM reasoning.

Plug and play with AI agents
Connect to any agent runtime that supports MCP, including Claude, OpenAI, Cursor, and custom setups.
Structured JSON responses
Get clean, consistent, and compact JSON that is ready for downstream LLM reasoning without brittle parsing or scraping.
Built-in support for research workflows
Use MCP to power agent-assisted analysis, dashboards, and research loops without building extra orchestration layers.

Open MCP guide

Live MCP Demo

Agent asks for research, MCP tools fetch the data, then the answer is composed from structured results.

30+ Years of Financial Data You Can Trust

Explore decades of structured statements, market data, and filing evidence built for research teams, financial products, and AI applications.

30+ Years of History
Long historical coverage since early 1990s.
20,000+ Companies
Global company data across major exchanges.
10M+ Data Points
Updated daily with structured delivery.

Annual

Quarterly

Show YoY

No data

SEC Filings For Research and Compliance Workflows

Access structured filing metadata across major form types, including annual reports, quarterly reports, current events, proxy materials, and registration statements. Use it to power compliance checks, filing timelines, governance workflows, and agent-assisted document retrieval.

Broad form coverage
Work with forms like 10-K, 10-Q, 8-K, DEF 14A, S-1, and more through one consistent API pattern.
Timeline-ready metadata
Each filing includes the form type, filing date, accession number, and report period for downstream workflows.
Useful for agents
Agents can filter form types, find the latest filing, and hand off URLs into retrieval or summarization pipelines.

Date	Form	Accession	Link

Why teams trust the dataset

Start with the provenance, coverage, and support details buyers usually need before they put financial data into production.

Provenance

See where the data comes from

Review how ApiFinance AI links normalized fields back to source filings and market datasets before you build research or compliance workflows.

Review data provenance

Coverage

Verify what the API covers

Check endpoint categories, historical ranges, and supported workflows before you commit engineering time to an integration.

Review data coverage

Support

Talk to the team before rollout

Use the contact page for enterprise questions, source validation, onboarding help, or contract discussions before you ship to production.

Contact ApiFinance AI

Start Building in Minutes

Use the official Python SDK to make a working request in minutes, then scale into scripts, services, and internal tools.

quickstart.py

import requests

Runtime

Interpreter

Python SDK

Mode

Autocomplete + live typing

Hint

Typed snippets mirror real SDK calls

View Python SDK

import requests

API_KEY = "your_api_key"
BASE_URL = "https://api.apifinance.ai"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

search = requests.get(
    f"{BASE_URL}/securities/search",
    headers=HEADERS,
    params={"query": "nvidia", "page": 1, "per_page": 10},
).json()

quote = requests.get(
    f"{BASE_URL}/securities/AAPL/quote",
    headers=HEADERS,
).json()

valuation = requests.get(
    f"{BASE_URL}/securities/AAPL/valuation",
    headers=HEADERS,
).json()

income_statements = requests.get(
    f"{BASE_URL}/statements/income",
    headers=HEADERS,
    params={"ticker": "AAPL", "timeframe": "annual", "limit": 5},
).json()

filings = requests.get(
    f"{BASE_URL}/sec_filings",
    headers=HEADERS,
    params={"ticker": "AAPL", "form": "10-K", "page": 1, "per_page": 10},
).json()

Frequently Asked Questions

Quick answers about dataset quality, MCP usage, SDK support, and production readiness.

Ready to Build Investor-Grade Workflows?

Join teams building finance products, analyst tools, and internal workflows on top of apifinance.ai.

Get Your Free API Key View API Docs