D

Data Aggregator

MCP server · by musharna

Data & Analytics Python v0.72.0

Find & fetch research datasets across 20 archives, omics registries, and literature sources.

View source ↗ Generate config for multiple servers More servers

Install

Run one of the commands below, then pick your client in the next section.

Python
uvx data-aggregator-mcp

Setup by client

Pick your client — the config below is generated for this server (local stdio).

claude_desktop_config.json

{
  "mcpServers": {
    "data-aggregator-mcp": {
      "command": "uvx",
      "args": [
        "data-aggregator-mcp"
      ],
      "env": {
        "NCBI_API_KEY": "<YOUR_NCBI_API_KEY>",
        "LLM_API_KEY": "<YOUR_LLM_API_KEY>",
        "EMBEDDING_API_KEY": "<YOUR_EMBEDDING_API_KEY>",
        "DATA_GOV_API_KEY": "<YOUR_DATA_GOV_API_KEY>"
      }
    }
  }
}

Format verified against the official Claude Desktop docs ↗.

Environment variables

Defined in the server's official registry manifest. Required secrets are shown as <YOUR_…> placeholders in the configs above.

  • NCBI_API_KEY secret — Optional NCBI E-utilities API key; raises the rate limit 3->10 req/s for omics, literature, and taxonomy lookups.
  • LLM_API_BASE — Base URL of an OpenAI-compatible /chat/completions endpoint; enables search(understand=true) and search(multi_query=true).
  • LLM_API_KEY secret — Bearer token for the LLM endpoint (LLM_API_BASE); omit for keyless local servers.
  • LLM_MODEL — Model name passed to the LLM endpoint (default: gpt-4o-mini); set to whatever your endpoint serves.
  • EMBEDDING_API_BASE — Base URL of an OpenAI-compatible /embeddings endpoint; enables search(rank=semantic) re-ranking.
  • EMBEDDING_API_KEY secret — Bearer token for the embeddings endpoint (EMBEDDING_API_BASE); omit for keyless local servers.
  • EMBEDDING_MODEL — Model name passed to the embeddings endpoint (default: text-embedding-3-small).
  • DATA_GOV_API_KEY secret — Optional api.data.gov key for the data.gov source; without it requests fall back to the shared public DEMO_KEY, which is aggressively rate-limited.

About this server

Distributed as Python, listed under Data & Analytics. Review our MCP security guide before granting access to real data.

Frequently asked questions

How do I install Data Aggregator?

Run the install command shown above, then paste the config for your client (Claude Desktop, Claude Code, Cursor, VS Code or Windsurf) into its MCP settings and restart the client.

Is Data Aggregator free to use?

The MCP server itself is free to install. The source is public on https://github.com/musharna/data-aggregator-mcp. Any third-party service it calls may require its own API key and account.

Which clients support Data Aggregator?

Any MCP-compatible client can use it, including Claude Desktop, Claude Code, Cursor, VS Code, Windsurf and custom agents.

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