biolit

mcp-name: io.github.rachadele/biolit

LLM-assisted biomedical literature screening and structured extraction. Accepts PubMed alert emails and mixed lists of PMIDs, DOIs, and GEO accessions in any combination. Retrieves full text from PMC, Europe PMC, bioRxiv/medRxiv, Unpaywall, and Semantic Scholar. Supports multiple LLM providers and exposes all functionality as an MCP server.

Setup

Requirements: Python 3.8+

Install from PyPI:

pip install biolit

Or install from source for development:

pip install -e .

Copy .env.example to .env and add your API key:

cp .env.example .env
# edit .env and set ANTHROPIC_API_KEY (or OPENAI_API_KEY)

On macOS, you can store the key in the system keychain instead of .env. biolit consults the keychain by service name only (no account required):

security add-generic-password -s ANTHROPIC_API_KEY -w
# or for OpenAI:
security add-generic-password -s OPENAI_API_KEY -w

Omit -w <value> to be prompted for the key without echoing it. The keychain is checked first; the env var is used only as a fallback (so a stale value in .env cannot mask a working keychain entry).

Usage

The tool accepts a PubMed alert email (.eml) or a plain-text file of identifiers, as well as inline identifiers via --ids. Identifiers can be PMIDs, DOIs, or GEO accessions — mixed lists are supported in a single run.

Use --default to run with schizophrenia genomics defaults (no prompts):

biolit docs/alert.eml --default
biolit docs/pmids.txt --default
biolit docs/geo_accessions.txt --default
biolit --ids 41795042,41792186,GSE53987 --default
biolit --ids 10.1101/2025.03.17.25324098 --default

Or specify criterion and fields as flags:

biolit identifiers.txt \
  --criterion "Is this about treatment-resistant schizophrenia?" \
  --fields "methodology, sample_size, treatment, outcomes"

Add --markdown (or --md) to also write a prose .md summary alongside the CSV. Each record gets a markdown section with ### field subsections; records that failed or were skipped appear as stub entries:

biolit refs.bib --config my_config.json --markdown
biolit refs.bib --config my_config.json --markdown --markdown-max-tokens 2048

Add --batch to issue screening, extraction, and markdown rendering through the provider's Message Batches / Batch API instead of one call per record. Per-request cost drops by ~50%, but each batch blocks on completion (typically several minutes per stage; up to 6 hours), so it's intended for the bulk weekly-alert case rather than one-off lookups. Anthropic and OpenAI only — falls back to sequential calls on Ollama or on OpenAI-compatible endpoints with a custom base_url. Also accepted as "batch": true in a config file.

biolit docs/alert.eml --default --batch
biolit docs/alert.eml --default --batch --markdown   # batches markdown too

Or use a JSON config file to store reusable parameters (CLI flags take precedence). The config can include ids or input_file (path to an .eml, .bib, or identifier list), and "markdown": true to enable markdown output:

biolit alert.eml --config my_config.json
biolit refs.bib --config my_config.json   # DOIs extracted from .bib automatically
biolit --config my_config.json            # ids or input_file supplied by config

The fields key in a config file can be a comma-separated string or a JSON object mapping field names to extraction descriptions. When a string is used, an extra LLM call converts the field names into des

... View full README on GitHub