31 MCP tools for ESG data extraction, PDF processing, vector search, and EU regulation analysis.
ESG MCP Servers is an MCP integration. 31 MCP tools for ESG data extraction, PDF processing, vector search, and EU regulation analysis.
The published pypi package is esg-mcp-servers, version 0.1.2. Its declared MCP transport is stdio.
The package declares ANTHROPIC_API_KEY (required): Anthropic API key — required for RAG queries and LLM-based metric extraction; POSTGRES_DSN (required): PostgreSQL connection string with pgvector extension (e.g. postgresql://esg:esg@localhost/esg_platform); MONGODB_URI (required): MongoDB connection string for PDF binary storage via GridFS (e.g. mongodb://localhost:27017); EMBEDDING_MODEL: Sentence-transformer model name for embedding generation (default: Snowflake/snowflake-arctic-embed-l-v2.0); EMBEDDING_DIMENSIONS: Embedding vector dimension size (default: 1024).
Check the maintainer’s instructions for account access, authentication and the supported client configuration. Once connected, inspect the tools your client receives and try a small task that matches the server’s stated purpose. The registry description does not include a verified, complete tool list.
View the publisher’s registry entry · Project repository. This profile uses version 0.1.2 from the registry. Registration identifies the publisher namespace; it does not establish that this is a first-party integration for every service it connects.
Browse related ai & ml services MCP servers for tools that cover the same kind of work.
| Variable | Description | Required |
|---|---|---|
| ANTHROPIC_API_KEY | Anthropic API key — required for RAG queries and LLM-based metric extraction | Yes |
| POSTGRES_DSN | PostgreSQL connection string with pgvector extension (e.g. postgresql://esg:esg@localhost/esg_platform) | Yes |
| MONGODB_URI | MongoDB connection string for PDF binary storage via GridFS (e.g. mongodb://localhost:27017) | Yes |
| EMBEDDING_MODEL | Sentence-transformer model name for embedding generation (default: Snowflake/snowflake-arctic-embed-l-v2.0) | Optional |
| EMBEDDING_DIMENSIONS | Embedding vector dimension size (default: 1024) | Optional |
The original Chromium automation reference server — simple, screenshot-driven browser control.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Workers, KV, R2 and D1 by conversation — Cloudflare's official remote servers for building and observability.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.