Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"esg-pdf": {
"command": "esg-pdf-processor"
},
"esg-metrics": {
"command": "esg-metrics-extractor"
},
"esg-scraper": {
"command": "esg-scraper"
},
"esg-vectors": {
"command": "esg-vector-store"
},
"esg-regulations": {
"command": "esg-regulations"
}
}
}Are you the author?
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Open-source Model Context Protocol servers for ESG (Environmental, Social, and Governance) data extraction, analysis, and regulation management.
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Open-source Model Context Protocol servers for ESG (Environmental, Social, and Governance) data extraction, analysis, and regulation management.
31 tools across 6 servers — install once, run only what you need.
Author: Ioannis Michos (johnmichos.tf@gmail.com)
pip install esg-mcp-servers
| Service | Required for |
|---|---|
| PostgreSQL 16 + pgvector | Vector storage, metrics, regulations |
| MongoDB 7 | PDF binary storage (GridFS) |
| Anthropic API key | RAG queries, metric extraction |
Spin up local databases with Docker:
docker compose up -d
Run the database migration:
esg-mcp-migrate
Copy .env.example and fill in your values:
cp .env.example .env
Key variables:
| Variable | Default | Description |
|---|---|---|
POSTGRES_DSN | postgresql://esg:esg@localhost/esg_platform | PostgreSQL connection string |
MONGODB_URI | mongodb://localhost:27017 | MongoDB connection string |
ANTHROPIC_API_KEY | — | Required for RAG and LLM extraction |
EMBEDDING_MODEL | Snowflake/snowflake-arctic-embed-l-v2.0 | Sentence-transformer model |
EMBEDDING_DIMENSIONS | 1024 | Embedding vector size |
ESRS-aligned KPI extraction for emissions, energy, water, waste, social, and governance domains.
| Tool | Description |
|---|---|
extract_emissions_data | GHG Scope 1, 2, 3 extraction |
extract_energy_data | Energy consumption & renewables (ESRS E2) |
extract_water_data | Water withdrawal, discharge, consumption (ESRS E3) |
extract_waste_data | Waste generation, recycling, landfill (ESRS E5) |
extract_social_data | Workforce, diversity, H&S (ESRS S1) |
extract_governance_data | Board composition & governance (ESRS G1) |
answer_esg_query | Free-text RAG Q&A over documents |
keyword_similarity_search | Semantic keyword search in documents |
detect_query_domain | Classify query into ESG domain |
detect_emissions_query_type | Detect emissions scope/year from query |
batch_extract_metrics | Extract all KPIs and persist to DB |
PDF validation, text/table extraction, and embedding generation.
| Tool | Description |
|---|---|
verify_esg_report | RandomForest ESG report classifier |
extract_text_chunks | Extract and chunk PDF text |
extract_tables | Table extraction with OCR fallback |
generate_embeddings | Batch embedding generation |
process_pdf_full_pipeline | End-to-end: extract, embed, store |
pgvector CRUD operations for document chunks and query cache.
| Tool | Description |
|---|---|
upsert_document_chunks | Insert/update chunks with embeddings |
similarity_search | Cosine similarity search |
get_cached_query_response | Retrieve cached LLM responses |
cache_query_response | Store LLM response in cache |
list_documents | List indexed documents |
EU ESG regulation download, ingestion, and semantic search.
| Tool | Description |
|---|---|
download_regulation | Download regulation PDF from EUR-Lex |
download_all_regulations | Batch download all configured regulations |
ingest_regulation | Extract, parse articles, embed, store |
search_regulation_text | Semantic search across regulation articles |
list_regulations | List ingested regulations |
ESG report discovery and download from the web.
| Tool | Description |
|---|---|
search_esg_reports | Multi-engine search for ESG PDFs |
crawl_company_website | Deep-crawl website for PDF links |
download_pdf | Download P |