US ESG Scores — Disclosures, Ratings & Sector Benchmarks (Top 1,000)

DatasetCSV.GZOpenFinanceESGSustainabilityGovernanceFactorsFree

Environmental, Social, and Governance scores for the top 1,000 US-listed issuers by market cap (approximating the Russell 1000). Three complementary files: (1) esg_disclosures — 68,097 per-filing E/S/G/composite scores across 978 companies, linked back to the originating SEC form. (2) esg_ratings — 18,099 per-fiscal-year ESG risk-rating letters (A–F scale) plus industry rank, across 967 companies. (3) esg_sector_benchmark — 6,640 sector-level annual averages for benchmarking. ESG data of this quality is typically paywalled by MSCI / Sustainalytics; this dataset gives you an open, reproducible alternative. Read with pandas.read_csv(path, compression='gzip', parse_dates=['date']). Useful for: ESG-tilted portfolio construction, sustainability research, regulatory disclosure analysis, and training models that need ESG features.

Use Cases

ESG-tilted portfolio construction and exclusion screens
Sustainability factor research and ESG-momentum signals
Sector-relative scoring (compare company score to benchmark)
Regulatory and stakeholder disclosure analysis
Training ML models with open ESG features (vs paywalled providers)

Methodology

Universe: top 1,000 US-listed issuers by market cap (NASDAQ/NYSE/AMEX), approximating Russell 1000. Three FMP endpoints: /stable/esg-disclosures (per-filing scores), /stable/esg-ratings (per-fiscal-year letter), /stable/esg-benchmark (annual sector averages, years 2018–2024). Scores are reported on the 0–100 scale where higher is better. Risk-rating letters use Sustainalytics-style A–F.

Update Schedule

Static snapshot. Re-run annually after new 10-K and ESG disclosures land.

Attribution

Source: ESG disclosures and risk ratings via Financial Modeling Prep.

Schema

name	type
symbol	string
date	date
acceptedDate	date
cik	string
companyName	string
formType	string
environmentalScore	number
socialScore	number
governanceScore	number
ESGScore	number
url	string

Sample Data

cik	url	date	symbol	ESGScore	formType	companyName	socialScore	acceptedDate	governanceScore	environmentalScore
0001090872	https://www.sec.gov/Archives/edgar/data/1090872/000109087226000064/0001090872-26-000064-index.htm	2026-07-31	A	70.02	10-Q	Agilent Technologies, Inc.	69.77	2026-09-01	63.29	77.02
0001090872	https://www.sec.gov/Archives/edgar/data/1090872/000109087226000055/0001090872-26-000055-index.htm	2026-04-30	A	69.66	10-Q	Agilent Technologies, Inc.	69.21	2026-06-01	63.34	76.42
0001090872	https://www.sec.gov/Archives/edgar/data/1090872/000109087226000023/0001090872-26-000023-index.htm	2026-01-31	A	69.55	10-Q	Agilent Technologies, Inc.	69.5	2026-03-03	63.01	76.14

Get this via API

# 1. Add dAgentBase once, in any MCP client. No install, no vendor keys.
#    Claude.ai / Claude Desktop: Settings -> Connectors -> Add custom connector
#    Cursor / Claude Code / others: mcp.json
{
  "mcpServers": {
    "dagentbase": {
      "url": "https://dagentbase.com/api/mcp",
      "headers": { "Authorization": "Bearer dm_live_YOUR_KEY" }
    }
  }
}

# 2. Then ask your agent, in plain language:
#    "Preview 'US ESG Scores — Disclosures, Ratings & Sector Benchmarks (Top 1,000)' and, if it fits, claim it and download the files."
#    Tools it will use: search_listings -> preview_listing -> purchase_listing -> get_download_urls

# 1. Add dAgentBase once, in any MCP client. No install, no vendor keys.
#    Claude.ai / Claude Desktop: Settings -> Connectors -> Add custom connector
#    Cursor / Claude Code / others: mcp.json
{
  "mcpServers": {
    "dagentbase": {
      "url": "https://dagentbase.com/api/mcp",
      "headers": { "Authorization": "Bearer dm_live_YOUR_KEY" }
    }
  }
}

# 2. Then ask your agent, in plain language:
#    "Preview 'US ESG Scores — Disclosures, Ratings & Sector Benchmarks (Top 1,000)' and, if it fits, claim it and download the files."
#    Tools it will use: search_listings -> preview_listing -> purchase_listing -> get_download_urls

Free

one time · open license

Details

Date Range2018-01-01 — 2026-09-05

Rows92,836

Size2 MB

Files3

FormatCSV.GZ

Available formats

CSV.GZ3 files · 2 MB

Freeopen