🔎 data-aggregator-mcp

One MCP server to find and fetch research data across archives, omics registries, and literature — behind a single normalized model.

search one query across Zenodo, DataCite (Dryad / Figshare / Dataverse / OSF / Mendeley), NCBI omics (GEO / SRA / BioProject), and literature (PubMed / OpenAIRE) — deduplicated, normalized, and cross-linked. resolve any hit to its file manifest, citation, and the data it points at. fetch it to disk with checksum verification.

mcp-name: io.github.musharna/data-aggregator-mcp

✨ Why this

Most data MCPs wrap a single source. This one unifies them behind four tools and one DataResource model, so an agent searches once and gets back comparable records:

• Multi-domain, one model — generalist archives + raw omics + literature, deduplicated by DOI (the fetchable record wins over bare metadata).

• Taxonomy synonym expansion — organism="Orobanche aegyptiaca" also matches Phelipanche aegyptiaca (NCBI Taxonomy), so a species rename doesn't cost you results.

• Paper → data bridge — resolve a paper and get links to the GEO / SRA / BioProject / DataCite records it produced.

• Verified fetch — streams to disk with md5 verification where the source exposes a checksum, optional archive unpacking, and a fail-loud integrity sniff that rejects an HTML paywall page served as a "PDF".

• Citations, access & full text — render a citation in any CSL style, get normalized access/license, and pull open-access full text — all in one resolve.

⚡ Quickstart

Run with no install:

uvx data-aggregator-mcp

Register with Claude Code:

claude mcp add data-aggregator -- uvx data-aggregator-mcp

A typical agent flow:

search("drought stress RNA-seq", organism="Sorghum bicolor")
  → [ geo:GSE..., sra:SRX..., zenodo:..., pubmed:... ]   # deduped, taxa-normalized

resolve("sra:SRX079566")
  → DataResource{ files: [ENA FASTQ urls…], access: "open", taxa: [...] }

fetch("sra:SRX079566", dest="./data")
  → ["./data/SRX079566_1.fastq.gz", …]                   # md5-verified

pip install data-aggregator-mcp
data-aggregator-mcp        # or: python -m data_aggregator_mcp

Add to a client's MCP config (e.g. Claude Desktop claude_desktop_config.json):

{
  "mcpServers": {
    "data-aggregator": {
      "command": "uvx",
      "args": ["data-aggregator-mcp"],
      "env": { "NCBI_API_KEY": "your-optional-key" }
    }
  }
}

🗂️ Sources

¹ Dryad downloads are token / bot-challenge gated, so fetch fails loud; resolve still lists the files. ² No upstream checksum — fetch verifies content-type instead (rejects an HTML page served in place of a binary).

🛠️ Tools

search(query, size?, sources?, organism?)

Fan out across all wired sources in parallel and return compact DataResource records, deduped by DOI. Per-source failures land in errors{} — never silently dropped.

• organism — expand the query with NCBI-Taxonomy synonyms; the expansion is echoed in taxon_expansion, and results carry normalized taxa[] ({taxid, name}) plus a described_in link to plant-genomics-mcp for plant taxa.

• sources — restrict the fan-out, e.g. ["omics"].

• size — max results (1–50).

resolve(id)

Full record + files manifest. Routes by id shape — zenodo:7654321, a bare DOI, datacite:10.5061/dryad.x, an omics id (sra:SRX079566, geo:GSE332789, bioproject:PRJNA1468572), or a literature id (pubmed:34320281, openaire:<id>). Attaches, where available:

• files[] — ENA FASTQ manifest (SRA), GEO suppl/, or the host repo's native manifest (Figshare / Dataverse / OSF / Dryad).

• links[] — paper → data: pubmed: → sra: / geo: / bioproject: (NCBI elink); openaire: → datacite: (ScholeXplorer Scholix).

• access / license — normalized status (open / embargoed / restricted / closed / unknown) and license where the source exposes it.

• identifiers — normalized {pmid, pmcid, doi}, plus an open-access full-text FileEntry (EuropePMC XML, or an Unpaywall PDF fallback) for papers.

• citation — pass cite=<format>: bibtex, ris, csl-json, or any CSL style name (apa, mla, vancouver, …). DOI records use content negotiation; others render CSL-JSON from metadata. Off by default; failures degrade quietly.

fetch(id, dest?, files?, max_bytes?, force?, extract?)

Download files to disk and return their paths. Streams under a max_bytes guard (force to override) with md5 verification wherever a checksum exists.

• files — restrict to a subset of the resolved manifest.

• extract — unpack downloaded zip / tar archives in place, guarded against path traversal and runaway extracted size. Off by default.

• Unverified fetches (GEO suppl/, literature full text) get a content-type sniff that fails loud if a declared binary is actually an HTML page.

• Fetchable: Zenodo, SRA, GEO, DataCite-hosted Figshare / Dataverse / OSF, and literature open-access full text. Dryad and other DataCite repos are discovery-only and raise FetchNotSupportedError.

list_sources()

Wired sources with their capabilities — layer, kinds, supported filters, fetchability, id examples, auth, and rate limits.

⚙️ Configuration

Both optional, set via environment variables:

• NCBI_API_KEY — raises the NCBI E-utilities rate limit (3 → 10 req/s) used by the omics, literature, and taxonomy lookups.

• UNPAYWALL_EMAIL — enables the Unpaywall fallback leg of literature full-text retrieval (the EuropePMC leg works without it).

🧪 Develop

uv venv && uv pip install -e ".[dev]"
uv run pytest -q
uv run ruff check src tests
DATA_AGGREGATOR_MCP_LIVE=1 uv run pytest -k live -q   # real-API probes

The README demo (examples/assets/demo.svg) is recorded network-free from examples/_demo_stdio.py — see the header of that file to re-record.

License

MIT — see LICENSE.