ESG MCP Servers
31 MCP tools for ESG data extraction, PDF processing, vector search, and EU regulation analysis.
Connector by freminder · GitHub account verified by the MCP Registry
Install
Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.
npx agentmarket install connector/freminder-esg-mcp-servers
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Reviews
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Permissions
What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.
- Tools
- 21 read · 6 write · 0 delete · 4 not yet classified
- Secrets
- 1 (API keys, tokens or passwords)
- Install scripts
- Not scanned yet
- Runs as
- Python package
Tools by what they do 31
Read from the source code; the running server may list different tools.
Read 21 · Look things up without changing anything.
answer_esg_querybatch_extract_metricsdetect_emissions_query_typedetect_query_domainextract_emissions_dataextract_energy_dataextract_governance_dataextract_social_dataextract_tablesextract_text_chunksextract_waste_dataextract_water_data
Show 9 more tools
get_cached_query_responseget_scraping_statuskeyword_similarity_searchlist_documentslist_regulationssearch_esg_reportssearch_regulation_textsimilarity_searchverify_esg_report
Write 6 · Create, change, send or run things.
cancel_scraping_jobdownload_all_regulationsdownload_pdfdownload_regulationprocess_pdf_full_pipelineupsert_document_chunks
Not yet classified 4 · We could not tell from the name and description.
cache_query_responsecrawl_company_websitegenerate_embeddingsingest_regulation
Secrets and settings it asks for
Secrets: values you paste in that let it act as you.
ANTHROPIC_API_KEY
Other settings (environment variables or headers).
EMBEDDING_DIMENSIONSEMBEDDING_MODELMONGODB_URIPOSTGRES_DSN
Tools (31)
Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].
answer_esg_queryAnswer a free-text ESG question about a document using Claude + RAG.
batch_extract_metricsExtract all standard ESG KPIs from a document and persist to esg_metrics.
cache_query_responseStore an LLM response in the query cache.
cancel_scraping_jobCancel an in-progress scrape job.
crawl_company_websiteDeep-crawl a company website to discover all PDF links. Use use_selenium=true for JavaScript-heavy sites.
detect_emissions_query_typeClassify if a query is emissions-specific and extract year/scope.
detect_query_domainClassify an ESG query into its domain (emissions, energy, water, waste, social, governance, general).
download_all_regulationsBatch download all configured EU ESG regulations and Omnibus documents.
download_pdfDownload a PDF from a URL and store it in MongoDB GridFS.
download_regulationDownload a specific EU ESG regulation PDF from EUR-Lex by CELEX number or short name (e.g. 'CSRD', '32022L2464').
extract_emissions_dataExtract GHG Scope 1, 2, 3 emissions values from a document.
extract_energy_dataExtract energy consumption and renewable energy KPIs (ESRS E2) from a document.
extract_governance_dataExtract board composition and governance KPIs (ESRS G1) from a document.
extract_social_dataExtract workforce, diversity, and health & safety KPIs (ESRS S1) from a document.
extract_tablesExtract ESG tables from a PDF using text patterns and OCR fallback.
Show 16 more tools
extract_text_chunksExtract text from a PDF and split into overlapping chunks.
extract_waste_dataExtract waste generation, recycling, and landfill KPIs (ESRS E5) from a document.
extract_water_dataExtract water withdrawal, discharge, and consumption KPIs (ESRS E3) from a document.
generate_embeddingsGenerate embeddings for text chunks.
get_cached_query_responseRetrieve a cached LLM response for a query.
get_scraping_statusGet the current status of a running scrape job.
ingest_regulationProcess a downloaded regulation: extract text, parse articles, generate embeddings, and store in pgvector.
keyword_similarity_searchFind semantically similar keyword mentions in a document.
list_documentsList all indexed documents, optionally filtered by company.
list_regulationsList all downloaded and ingested regulations with metadata.
process_pdf_full_pipelineRun the complete pipeline: extract text/tables, embed, store in pgvector. Returns document_id.
search_esg_reportsSearch for ESG/sustainability PDF reports for a company using Google, Bing, and DuckDuckGo.
search_regulation_textSemantic search across regulation articles using pgvector. Optionally filter by regulation short name or requirement type.
similarity_searchFind the top-k most semantically similar chunks to a query embedding.
upsert_document_chunksInsert or update document text chunks with embeddings into pgvector. Each chunk must have: content (str), embedding (list[float]), chunk_index (int). Optional: page_number (int), content_type ('text'|'table').
verify_esg_reportUse the RandomForest classifier to determine if a PDF is an ESG report.
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Weekly downloads
- 30
- Last commit
- Feb 28, 2026 (8 months ago)
- Last release
- Feb 28, 2026 (8 months ago)
- Last package publish
- Feb 28, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026) and the package registry.
Details
- Registry name
io.github.freminder/esg-mcp-servers- Version
- 0.1.2
- Auth
- API key
- Packages
- pypi esg-mcp-servers
- License
- MIT
- Repository
- github.com/freminder/esg-mcp-servers
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
Cite this page
ESG MCP Servers. Agent Mart. https://agentmart.dev/connectors/freminder-esg-mcp-servers (last updated 2026-10-24)