mcpField
R
Research Chain

Research Chain

Remote
pipeworx.ioScience & Education0Updated 5w ago

About Research Chain

Research Chain is an MCP server for researchers and agents that gathers a paper’s metadata, open copies, datasets, code, citations, and retraction indicators from a DOI, PMID, or arXiv ID. It combines multiple scholarly sources in one call and reports partial failures rather than silently dropping them.

Key features

  1. 01Look up papers by DOI, PMID, or arXiv ID
  2. 02Retrieve open copies and stated licenses
  3. 03Find related datasets and software
  4. 04Search code and citing papers
  5. 05Report retraction indicators and source failures

Use cases

  1. 01Check whether a paper has a free copy and stated license
  2. 02Find datasets or code associated with a paper
  3. 03Review citations and retraction records

MCP support

Exposes the `research_chain` tool to MCP clients, with a gateway endpoint and a standalone stdio server. The gateway connection also lists shared Pipeworx meta-tools.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://gateway.pipeworx.io/research-chain/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

@pipeworx/research-chain

Everything openly available around one academic paper, in a single call: full text, license, datasets, code, and citations. Given a DOI, PMID, or arXiv id, research_chain walks the join that Crossref, OpenAlex, Unpaywall, DataCite, Zenodo, Hugging Face Papers, PubMed Central, and Semantic Scholar each expose piecemeal — so a caller no longer has to know all six/seven tools to answer "what datasets and code are linked to this paper?" or "find an open copy of this DOI and its license."

Part of Pipeworx — an MCP gateway connecting AI agents to 1683+ live data sources.

Tools

  • research_chain({doi | pmid | arxiv_id, max_datasets?, max_citing?}) — returns:
    • paper — title, journal, publisher, authors, Crossref's stated license(s) (URL + which manuscript version each applies to), OpenAlex concepts and citation count.
    • open_copies[] — every open-access location Unpaywall knows about, each with its OWN host_type, version (publishedVersion | acceptedVersion | submittedVersion), and license — never collapsed. is_oa: true only means "a free-to-read copy exists somewhere"; it says nothing about reuse rights, which is why license is null (not guessed) whenever Unpaywall doesn't state one. A PubMed Central copy (if one exists) is added as its own entry with license and version explicitly null, since NCBI's ID Converter confirms the copy exists but doesn't state its terms.
    • pmc_full_text — {has_full_text, pmcid, pmid, url} from NCBI's ID Converter.
    • datasets — {total, returned, results[]} from DataCite's relatedIdentifiers search (datasets/software that cite the paper's DOI). total is the real upstream count even when results is truncated to max_datasets.
    • code — {zenodo[], paperswithcode}. Zenodo is searched by metadata.related_identifiers.identifier. paperswithcode (Hugging Face Papers, the de-facto successor) reports {found: false, results: []} when the upstream search comes back empty — an empty result is not_found, never treated as an answer (a bare [] from this upstream used to be routed to as if it were a real "no code exists" answer).
    • citing — {count, top[], note} from Semantic Scholar: count is the paper's total citation count, top is up to max_citing citing papers sorted by their own citation count. note carries an honest partial- failure message (e.g. a rate limit) when one of the two Semantic Scholar calls failed but the other succeeded — it is never silently dropped.
    • retraction — derived from the SAME Crossref record already fetched for paper (title marker, update-to retraction notices, is-retracted-by relation) — no extra API call. retracted: false means "no retraction on record", not proof the paper is clean (coverage depends on the publisher).
    • sources_used / sources_failed — every leg fetches independently and in parallel; a slow or dead upstream lands in sources_failed with a reason, and every other leg still returns.
    • as_of — ISO timestamp of the call.

Auth

Keyless. Every upstream here is a public, unauthenticated API. Crossref, OpenAlex, and the NCBI ID Converter ask only for a polite-pool contact email, which this pack supplies as its own ([email protected]) — the same pattern as the crossref, openalex, and unpaywall packs.

Data sources

OSF was scoped as a third code/materials source but dropped: its public API has no DOI-filterable field (/v2/preprints/?filter[doi]=... returns HTTP 400 "not a filterable field", verified live). Zenodo + Hugging Face Papers cover the code/materials join for now.

Identifier resolution

  • doi — used directly (a doi.org URL or doi: prefix is stripped).
  • pmid — resolved to a DOI via NCBI's ID Converter.
  • arxiv_id — resolved to arXiv's own auto-registered DataCite DOI (10.48550/arXiv.<id>), which covers essentially every arXiv submission since 2022. This is a construction, not a verified lookup — a pre-2022 arXiv id without a registered DOI will report not_found on the downstream legs rather than resolving.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "research-chain": {
      "url": "https://gateway.pipeworx.io/research-chain/mcp"
    }
  }
}
What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/research-chain/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1683+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

No MCP client? Call it over HTTP

curl -X POST https://gateway.pipeworx.io/v1/tools/research_chain \
  -H 'Content-Type: application/json' \
  -d '{"doi":"10.1038/s41586-020-2649-2"}'

No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/research_chain. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.

Standalone (no gateway account)

This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:

{
  "mcpServers": {
    "research-chain": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-research-chain"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-research-chain

It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call for only this pack's tools — none of the shared meta-tools the gateway connection above adds. Same source, same tools, no ask_pipeworx routing.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

ask_pipeworx({ question: "your question about Research Chain data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.