ESG MCP Servers

io.github.freminder/esg-mcp-servers · v0.1.2

31 MCP tools for ESG data extraction, PDF processing, vector search, and EU regulation analysis.

Source code Set it up

Connect Runs on your machine

Terminal

claude mcp add esg-mcp-servers -e ANTHROPIC_API_KEY=<ANTHROPIC_API_KEY> -e POSTGRES_DSN=<POSTGRES_DSN> -e MONGODB_URI=<MONGODB_URI> -e EMBEDDING_MODEL=<EMBEDDING_MODEL> -e EMBEDDING_DIMENSIONS=<EMBEDDING_DIMENSIONS> -- uvx esg-mcp-servers==0.1.2

claude_desktop_config.json

{
  "mcpServers": {
    "esg-mcp-servers": {
      "command": "uvx",
      "args": [
        "esg-mcp-servers==0.1.2"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "<ANTHROPIC_API_KEY>",
        "POSTGRES_DSN": "<POSTGRES_DSN>",
        "MONGODB_URI": "<MONGODB_URI>",
        "EMBEDDING_MODEL": "<EMBEDDING_MODEL>",
        "EMBEDDING_DIMENSIONS": "<EMBEDDING_DIMENSIONS>"
      }
    }
  }
}

~/.cursor/mcp.json

{
  "mcpServers": {
    "esg-mcp-servers": {
      "command": "uvx",
      "args": [
        "esg-mcp-servers==0.1.2"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "<ANTHROPIC_API_KEY>",
        "POSTGRES_DSN": "<POSTGRES_DSN>",
        "MONGODB_URI": "<MONGODB_URI>",
        "EMBEDDING_MODEL": "<EMBEDDING_MODEL>",
        "EMBEDDING_DIMENSIONS": "<EMBEDDING_DIMENSIONS>"
      }
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "esg-mcp-servers": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "esg-mcp-servers==0.1.2"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "<ANTHROPIC_API_KEY>",
        "POSTGRES_DSN": "<POSTGRES_DSN>",
        "MONGODB_URI": "<MONGODB_URI>",
        "EMBEDDING_MODEL": "<EMBEDDING_MODEL>",
        "EMBEDDING_DIMENSIONS": "<EMBEDDING_DIMENSIONS>"
      }
    }
  }
}

Replace the values in angle brackets with your own. Keys stay on your machine; we never see them.

Tools

This server runs locally, so its tools are listed by your MCP client once it starts.

Environment variables

Name	Description
`ANTHROPIC_API_KEY` Required, secret	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` Optional	Sentence-transformer model name for embedding generation (default: Snowflake/snowflake-arctic-embed-l-v2.0)
`EMBEDDING_DIMENSIONS` Optional	Embedding vector dimension size (default: 1024)

Details

Package	`[email protected]` (PYPI, stdio)
First published	28 Feb 2026
Last updated	28 Feb 2026
Registry name	`io.github.freminder/esg-mcp-servers`

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Local install

Installed and run on your own machine, so there is no public endpoint to check.

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