Dog Geroscience

Name: Dog Geroscience
Author: w0lph

@w0lphMCP server · External

Dog-specific aging tools: HAGR dog rows, dog orthologs, dose translation, DAP codebooks, FDA FOI.

Biology & genomicsv0.1.1MITPython

Freeno charge per call

How to install

Runs on your machine from its package; the steps are below.

What it does

Reads
Writes
High impact

Not assessed yet.

What it costs

Free

Odel charges nothing per call. The publisher may charge for its own service.

Runs locally over stdio

This server isn't hosted — your MCP client launches it from a package registry. Use one of the commands below, or drop the config into your client (e.g. Claude Desktop).

PyPIdog-geroscience-mcpv0.1.1

Run

uvx dog-geroscience-mcp

MCP client config

{
  "mcpServers": {
    "dog-geroscience": {
      "command": "uvx",
      "args": [
        "dog-geroscience-mcp"
      ]
    }
  }
}

README4 min readView on GitHub

k9 — AI tooling for canine longevity research

Research brief: canine-longevity-ai-opportunities.md (landscape, ranked opportunities, and the Phase 1 plan in Section 7).

Phase 1 components:

Directory	What	Status
corpus/	`canine-aging-corpus`: reproducible Europe PMC corpus of the canine aging literature (records, JATS→Markdown full text from Europe PMC or NCBI, manifest, version file).	Complete: 3,565 records (2,185 core); full text for 1,140 of 1,347 PMCIDs (the other 207 are publisher-restricted from XML distribution).
mcp/	`dog-geroscience-mcp`: MCP server with 18 dog-specific aging tools (AnAge/DrugAge/GenAge dog rows, dog orthologs via Ensembl with caching, FDA Km dose translation, Dog Aging Project codebooks across 9 releases, NIH RePORTER, BM25 corpus search with full-text retrieval, FOI summaries and structured records, the canine trial registry, intervention dossier).	Complete: 30 offline tests, smoke-tested against live Ensembl/RePORTER and over stdio; DB built from the finished corpus, FOI and trial-registry layers.
questions/	`canine-geroscience-questions`: 133 questions across 10 categories, each with a gold answer and a verbatim quote from a corpus record, enforced by a validator; plus a BM25 retrieval baseline.	v0.1: drafted, validator-clean, then reviewed item-by-item by an independent LLM pass (9 fixes, 1 drop); recall@5 = 0.985. No domain-expert review yet.

Phase 2 components:

Directory	What	Status
foi/	`foi-summaries`: FDA CVM Freedom of Information summaries as a public-domain dataset (index of 1,726 summaries, 497 dog-product PDFs, text, parsed sections and General Information fields, species flags) plus a typed, quote-validated extraction of all 497 summaries (1,026 PK values, 193 safety studies, 414 effectiveness studies, 918 adverse-reaction rows).	Complete: 497 records, 97% with parsed sections; structured layer covers all 497 (4,510 quotes, 0 errors, 79 explained warnings).
`mcp/` (extended)	`intervention_dossier` (synonym-aware, species-filtered), `foi_summary_search`, `foi_summary_get`, `foi_structured_search`, `canine_trial_search`, the `dossier_briefing` prompt; `scripts/dossier_eval.py` coverage table over ITP compounds.	Complete; 30 tests.
trials/	`canine-trials`: registry of interventional studies and cohorts on aging in dogs (lifespan, healthspan, cognition, mobility, immunosenescence, cancer prevention; lifetime cohorts; company programs such as STAY/LOY-002), one typed record per study with every field backed by a verbatim quote, and a validator (`ct validate`) that checks the quotes against the corpus, Europe PMC abstracts and page snapshots. Served as `canine_trial_search`, as site pages (`/trials/`) and as a Hub dataset.	v0 (2026-10-01): drafted from corpus abstracts by model-assisted extraction plus hand-written company records; validator-clean; no domain-expert review yet.

| docs/ | Static evidence site generated from the database by mcp/scripts/build_site.py: one page per NIA ITP compound and veterinary comparator (DrugAge rows, dog-equivalent doses, canine literature, FDA FOI summaries, gaps) and one per FOI ingredient (dose regimen, PK, target-animal safety, effectiveness, adverse reactions, each with its verbatim quote), plus llms.txt and a sitemap. No model-written text. | Live at https://w0lph.github.io/k9/ (219 pages); rebuild with cd mcp && uv run python scripts/build_site.py. |

.\rebuild.ps1 regenerates everything in dependency order (-Fresh re-fetches sources); scripts/refresh.sh is the same from a clean checkout and is what the monthly GitHub Actions workflow runs to republish the datasets, the database and the site. PUBLISHING.md is the step-by-step for the Hugging Face Hub (dataset cards and staging script in publish/), PyPI and the MCP registry (mcp/server.json), and Glama (glama.json, root Dockerfile). The server installs with uvx dog-geroscience-mcp (PyPI), as a Claude Desktop extension (.mcpb on the releases page), or as a Claude Code plugin with a routing skill (/plugin marketplace add w0lph/k9, then /plugin install dog-geroscience@k9; sources in plugins/), and downloads its database on first run. Each directory is its own uv project:

bash

cd corpus && uv sync --extra dev && uv run pytest -q
cd mcp && uv sync && uv run dog-geroscience-mcp build && uv run pytest -q
cd questions && uv sync && uv run pytest -q && uv run cgq validate data/canine_geroscience_v0.jsonl --require-ids
cd foi && uv sync && uv run foi run && uv run pytest -q
cd mcp && uv run dog-geroscience-mcp build --skip-download   # picks up ../foi/data/foi_summaries_dog.jsonl

Large derived data (corpus/data, mcp/data, FOI PDFs and text) is git-ignored; it is rebuilt by the pipelines and published as Hugging Face datasets (publish/).

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