Biolab MCP Server

Biolab MCP Server

*"AI agents querying biological databases leave no audit trail. Six months later, nobody can answer: what exact query returned this result, when, and was that paper peer-reviewed at the time? Biolab solves that."*

A local-first scientific evidence workspace with Python and Go clients. It sits between scientists or AI agents and PubMed, Europe PMC, ClinicalTrials.gov, UniProt, Open Targets, and bioRxiv/medRxiv. Every retrieval preserves its source response and returns a retrieval_id; projects, reviewed collections, evidence watches, and claim links build a traceable workflow on top.

New to MCP? It's an open standard that lets an AI assistant — Codex, ChatGPT, Claude, Cursor, and others — call external tools during a conversation. Add Biolab and the assistant can retrieve, preserve, organize, monitor, and cite scientific evidence while keeping every result inspectable later.

Use It Now — No Install

A hosted instance is available at https://srikarjy025-biolab-mcp.hf.space/mcp. Point your client at it and you're done. Hosted capabilities follow the version currently deployed there; run locally for the complete 0.4 workspace in this repository.

Claude Code:

claude mcp add --transport http biolab https://srikarjy025-biolab-mcp.hf.space/mcp

Claude Desktop / Cursor — add this to your MCP config file:

{

"mcpServers": { "biolab": { "url": "https://srikarjy025-biolab-mcp.hf.space/mcp" } } }

(Add `"headers": {"Authorization": "Bearer <your key>"}` alongside `"url"` once you have a key — see the rate-limit note below.)

The 0.4 server exposes unified search, source-specific search, standard search/fetch, retrieval inspection, projects, collections, watches, claims, and reports. Every retrieval is written to a hash-chained audit trail you can inspect later (see Audit Trail Schema below).

For cross-source research, search_evidence searches PubMed, Europe PMC, ClinicalTrials.gov, UniProt, and Open Targets through one call while preserving explicit results and errors for each source.

Also listed on the official MCP Registry and Smithery if you'd rather discover/install it from there.

A note on rate limits. The hosted server is shared and stays open — no signup required for casual use — but callers with no API key share one small, low-throughput budget (1 req/s to PubMed) so no single anonymous user can starve everyone else. If you're doing more than a handful of queries, ask for a key (below) and you get your own isolated, higher budget instead.

Getting a key:

Authorization: Bearer <your key>

Add that header in your client's MCP config (Claude Code: claude mcp add --transport http biolab --header "Authorization: Bearer "). Keys are issued with biolab keys create — see Managing API Keys below if you're running your own instance; otherwise ask the maintainer for one.

Want to run your own copy instead (local dev, your own storage, self-hosting)? Keep reading.

The Problem

A drug discovery team uses an AI agent to research gene targets. The agent queries PubMed 200 times over three days and surfaces a paper claiming gene X is upregulated in pancreatic cancer. A scientist makes a decision based on that. Six months later, during FDA submission:

• What exact query returned that paper?
• What date was it retrieved?
• Was it peer-reviewed at retrieval time, or a preprint published later?
• Did the agent summarize it accurately, or hallucinate details?

Without Biolab, nobody can answer any of those questions. The retrieval is invisible.

What Biolab Does

Biolab is an interception and logging layer, not a retrieval layer. It doesn't interpret evidence, rank it, or summarize it — it records what happened, verbatim, so an agent's claim can always be traced back to an unforgeable original.

Your AI Agent

↓ MCP tool call (e.g. search_pubmed) Biolab MCP Server ↓ HTTP Source API (PubMed, Europe PMC, ClinicalTrials.gov, bioRxiv/medRxiv) ↓ paper Biolab writes a hash-chained retrieval record to the audit database ↓ paper + retrieval_id Back to your agent

The agent gets the paper it asked for. Biolab gets a permanent, queryable, tamper-evident record of exactly what happened.

Sources Supported

All sources share a single audit database (SQLite locally, or Turso — a hosted, SQLite-compatible database — in production) with one source-agnostic schema.

Build It Yourself

You don't need to know Python or Go to get this running locally — just follow these steps in order. All commands are run in a terminal.

Prerequisites

• Python 3.11 or newer — check with python3 --version. Get it from python.org if you don't have it.
• Git — to download (clone) the code. Check with git --version.

That's genuinely it for the Python path — no database server to install, no API keys required (PubMed works anonymously, just at a lower rate limit).

1. Get the code

git clone https://github.com/srikarjy/biolab-mcp-server.git

cd biolab-mcp-server

2. Install it

python3 -m venv .venv          # creates an isolated Python environment

source .venv/bin/activate # on Windows: .venv\Scripts\activate pip install -e ".[dev]" # installs the package + test tools

Add the optional remote Turso driver only if needed: pip install -e ".[turso]"

3. Try it

biolab demo --query "BRCA1 pancreatic cancer"

This searches PubMed for real, stores every result in a local biolab.db file (created automatically, no setup needed), and prints back the retrieval_id for each paper — the same ID an AI agent would get back over MCP.

4. Run the test suite (optional, confirms everything works)

pytest -m "not live and not benchmark" -v

Run pytest -m live -v separately when network access and local socket binding are available. Those tests exercise real PubMed, Europe PMC, ClinicalTrials.gov, and bioRxiv services; the default command stays deterministic and offline.

5. Run it as an MCP server (what an AI agent actually connects to)

python -m biolab.server

This starts an HTTP server on http://localhost:8000/mcp — point Claude Desktop, Claude Code, or Cursor at that URL exactly like in Use It Now, just with localhost:8000 instead of the hosted URL.

6. Build the Docker image (optional)

If you'd rather not install Python locally at all:

docker build -f space/Dockerfile -t biolab-mcp .

docker run -p 8000:8000 biolab-mcp

(Storage defaults to an ephemeral file inside the container unless you set TURSO_DATABASE_URL/TURSO_AUTH_TOKEN — see Environment Variables below.)

Prefer a pre-built release?

pipx install biolab-mcp      # or: pip install biolab-mcp

# Or the Go binary, no Python required at all:

curl -L https://github.com/srikarjy/biolab-mcp-server/releases/latest/download/biolab_darwin_arm64.tar.gz | tar xz ./biolab search "BRCA1 pancreatic cancer" --max 3

Usage

CLI (Scientist-Friendly)

# Search several evidence sources in one audited workflow

biolab evidence "KRAS pancreatic cancer" \ --sources pubmed,europepmc,clinicaltrials,uniprot,opentargets --max 5

Search PubMed

biolab search "BRCA1 pancreatic cancer" --max 5

Search Europe PMC

biolab search-europepmc "BRCA1 pancreatic cancer" --max 5

Search ClinicalTrials.gov

biolab search-clinicaltrials "pancreatic cancer" --max 5

List bioRxiv preprints (no free-text search - API limitation)

biolab search-biorxiv neuroscience --max 10 biolab search-biorxiv all --server medrxiv --max 10

Retrieve full audit record

biolab get

List recent retrievals

biolab list --source pubmed --limit 10

Export for analysis

biolab export evidence.jsonl --source clinicaltrials

Verify the complete tamper-evident audit chain

biolab verify --db biolab.db

Run demo

biolab demo --query "BRCA1 pancreatic cancer"

Run the offline portfolio demo (no network or scientific claims)

biolab portfolio-demo

Run the real end-to-end scientist workflow against a local server

python scripts/scientist_workflow_demo.py --url http://127.0.0.1:8000

Start the private local dashboard and REST API

biolab web

Open http://127.0.0.1:8000

Create a project, organize evidence, and trace a claim

biolab projects create "KRAS target review" --description "Pancreatic cancer evidence" biolab collections create "Reviewed evidence" biolab collections add --relevance relevant --note "Reviewed" biolab claims create "KRAS is a therapeutic target" biolab claims link --stance supports --assessment human_reviewed

Monitor a source for added, removed, or revised records

biolab watches create pubmed "KRAS pancreatic cancer" biolab watches run-all

Export a complete project report

biolab projects report --output report.md

The dashboard binds to 127.0.0.1 by default. REST endpoints cover evidence, projects, collections, watches, claims, and reports. Discover them at /openapi.json; use /health, /metrics, and /v1/verify for operations. Run biolab web --require-auth with keys created by biolab keys create, or use BIOLAB_REQUIRE_AUTH=true on the unified MCP server, before exposing it remotely.

MCP Tools (Agent-Friendly)

// Search any source

{"name": "search_evidence", "arguments": {"query": "KRAS pancreatic cancer", "agent_id": "research:target-validation", "sources": ["pubmed", "europepmc", "clinicaltrials", "uniprot", "opentargets"], "max_results": 5}} {"name": "search_pubmed", "arguments": {"query": "BRCA1 pancreatic cancer", "agent_id": "aletheia:advocate", "max_results": 5}} {"name": "search_europepmc", "arguments": {"query": "BRCA1 pancreatic cancer", "agent_id": "aletheia:advocate", "max_results": 5}} {"name": "search_clinicaltrials", "arguments": {"query": "pancreatic cancer", "agent_id": "aletheia:advocate", "max_results": 5}} {"name": "search_biorxiv", "arguments": {"category": "neuroscience", "agent_id": "aletheia:advocate", "max_results": 5, "server": "biorxiv"}}

// Retrieve full audit record (works for ALL sources) {"name": "get_retrieval", "arguments": {"retrieval_id": "uuid-from-search"}}

BioClaw

A ready-to-copy BioClaw skill is included at integrations/bioclaw/biolab-evidence. It c