noodle-mcp
Noodle Biomedical Literature Discovery MCP — search papers and traverse citation or semantic literature graphs.
Documentation
Noodle Biomedical Literature Discovery MCP
The official public, read-only Model Context Protocol adapter for biomedical
literature discovery from Helena Bioinformatics.
Agents can select it from a user task even when the user does not know the
Noodle brand.
Public endpoint: `https://api.helena.bio/noodle/v1/mcp`
Official Registry identity: `io.github.helena-bioinformatics/noodle`
No account, API key, patient data, or private content is required or accepted.
What agents can do
- search a public PubMed-derived biomedical corpus by natural language, PMID,
DOI, or PMCID;
- retrieve source-linked publication records by PMID or Noodle work ID;
- traverse bounded citation and semantic neighborhoods from a publication;
- continue graph exploration through returned work identifiers while
preserving edge types and graph provenance;
- inspect corpus size, sources, freshness, coverage, and active graph metadata.
The seven published tools are `search_biomedical_literature`,
`get_publication_details`, `get_work_details`,
`get_publication_neighborhood`, `get_work_neighborhood`,
`get_corpus_summary`, and the separate explicit opt-in `support_helena`
information action.
Connect
Any MCP client that supports remote Streamable HTTP can use the endpoint. Exact
recipes for ChatGPT, Claude, Codex, VS Code, Cursor, Windsurf, Gemini CLI,
Grok, Perplexity, Microsoft Copilot Studio, Biomni, and Biorouter live under
`registry/platforms` and `integrations`.
Ready-to-use ecosystem packages are included for:
contract supported by the hosted service;
- Galaxy, with a Planemo-linted ToolShed
wrapper; and
- KNIME Analytics Platform, with a table-to-MCP
Python Script node and prepared Hub listing; and
Cytoscape GraphML workflow; and
- the companion Galaxy Training Network tutorial
for a Folklore-to-Noodle literature workflow.
The companion Agent Skill is in
`skills/noodle-biomedical-literature-discovery`. It enables implicit,
task-first selection for requests such as:
- “Find source-linked papers about BRCA1 homologous recombination.”
- “What publication is PMID 35008774?”
- “Show papers related to this article through citations and semantic
similarity.”
- “Walk two bounded hops from this work ID and preserve the edge types.”
Build the deterministic skill archive with:
python3 ops/package_agent_skill.pyGraph boundary
Start from a resolved PMID or work ID and request one bounded neighborhood at a
time. Report edges exactly as returned, keep a visited-ID set, and stop at a
missing neighborhood. Search rank, citation proximity, semantic similarity,
co-mention, and graph distance are discovery signals. They do not establish
causality, scientific validity, diagnosis, or treatment.
Development
Python 3.12 is required.
python -m venv .venv
. .venv/bin/activate
python -m pip install -r requirements-dev.lock
python -m pip install --no-deps -e .
pytest
ruff check .
ruff format --check .Run the brand-blind contract audit with:
python benchmarks/agent-discovery/audit_skill.pyThe benchmark contains 60 prompts that omit `Noodle`, `Helena`, and `MCP`.
It covers all six scientific routes plus negative and safety controls.
Agent Plugin and Kiro Power
This repository is also a portable Agent Plugin and Kiro Power. `plugin.json`
provides brand-blind activation keywords, the existing Agent Skill supplies the
scientific routing and safety boundary, and `mcp.json` connects directly to the
canonical hosted Streamable HTTP endpoint. The Power does not proxy, repackage,
or reimplement Noodle.
Privacy policy: https://noodle.helena.bio/privacy
Cite Noodle
The persistent Research Resource Identifier is
`RRID:SCR_028920`. Cite the resource in a
methods section as Noodle (RRID:SCR_028920). Use the
version DOI when a version-specific
software citation is also needed. The RRID identifies the resource across
publications, while the DOI identifies the archived 0.2.0 release.
Support: https://noodle.helena.bio/contact or `contact@helena.bio`
Public resources
- Hands-on tutorial: https://github.com/helena-bioinformatics/noodle-mcp/blob/main/docs/tutorials/biomedical-literature-discovery-and-graph-traversal.md
- Connector and agent-selection guide: https://noodle.helena.bio/mcp
- Client integrations: https://noodle.helena.bio/integrations
- Server Card: https://noodle.helena.bio/.well-known/mcp/server-card.json
- Official Registry: https://registry.modelcontextprotocol.io/v0/servers?search=io.github.helena-bioinformatics%2Fnoodle
- Citable release: https://doi.org/10.5281/zenodo.22166486
- Software Heritage archive request: https://archive.softwareheritage.org/api/1/origin/save/2457442/
- Software Heritage snapshot: https://archive.softwareheritage.org/swh:1:snp:09b8fb7c64de15487e873b4f77e3e4b57abc02fb/
- Methodology: https://noodle.helena.bio/methodology
License and security
Apache License 2.0. Report vulnerabilities privately as described in
`SECURITY.md`. Do not submit patient, private case, clinical-record, credential,
or private uploaded content to the public service or issue tracker.
Frequently asked questions
What is noodle-mcp?
noodle-mcp is Noodle Biomedical Literature Discovery MCP — search papers and traverse citation or semantic literature graphs.
How do I install noodle-mcp?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is noodle-mcp open source?
Yes — it is hosted on GitHub at https://github.com/helena-bioinformatics/noodle-mcp.
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