Mosaic Pre Clinical Intelligence vs Taiwan Health MCP
A side-by-side look at the Mosaic Pre Clinical Intelligence and Taiwan Health MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Mosaic Pre Clinical Intelligence for biology & bioinformatics work as a local process; choose Taiwan Health MCP for biology & bioinformatics. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Mosaic Pre Clinical Intelligence when
- You need dedicated capabilities in the Biology & Bioinformatics domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
DATABASE_URL, MOSAIC_API_KEY, MOSAIC_TIER. - You want tools like
mosaic_get_target_profile, mosaic_get_target_compounds, mosaic_get_coverage_grid.
Choose Taiwan Health MCP when
- You need dedicated capabilities in the Biology & Bioinformatics domain.
- Its auth model fits you: No auth required.
- You have the keys it needs:
POSTGRES_PASSWORD. - You want tools like
health_check, calculate_chads2_vasc, calculate_wells_pe.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Biology & Bioinformatics | Biology & Bioinformatics |
| Quality signal | 57/100 · Good | 60/100 · Good |
| Install command | Confirmed | Not confirmed yet |
| Transport | Local subprocess (stdio) | — |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | DATABASE_URLMOSAIC_API_KEYMOSAIC_TIER | POSTGRES_PASSWORD |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 167 |
| Directory activity | 3 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 11 | 59 |
| Full listing | View Mosaic Pre Clinical Intelligence | View Taiwan Health MCP |
Tools & capabilities
Mosaic Pre Clinical Intelligence tools 11
mosaic_get_target_profileGet a comprehensive intelligence dossier for a drug target. Returns UniProt biology, target scores, SAR summary, disease associations, validation evidence, pathways, PPIs, competitive landscape, clinical pipeline, and publication momentum. This is the primary tool for any target question.mosaic_get_target_compoundsGet compounds active against a specific drug target. Returns compounds with activity data (IC50, Ki, etc.), sorted by potency or, with sort='max_phase', approved and clinical drugs first. Unnamed research compounds read compound_name 'unnamed' with the ChEMBL id in chembl_id.mosaic_get_coverage_gridCoverage-honest grid for ANY human gene symbol - the live demo of the mechanism. In this self-hosted package the grid resolves identity (HGNC) and structure (AlphaFold DB) live; the remaining axes are marked `queued` and are computed by the hosted service's dossier pipeline (getmosaic.dev). Every count carries a state; nothing unfetched is a zero.mosaic_get_target_papersGet scientific papers about a specific drug target. Where the database carries PubTator3 gene annotations, only papers tagged with the target's NCBI Gene ID are served (`membership_basis` says which test applied), dated by the earliest of e-pub / issue / PubMed entry, papers naming the target in the title first.mosaic_get_target_structureGet the AlphaFold structural snapshot for a drug target. Returns AlphaFold model URLs (PDB / CIF / PAE), per-residue confidence summary (mean pLDDT, fractions of residues at high / confident / low confidence, disordered fraction), and protein length. Useful for SBDD scoping, disorder/IDR risk, and confidence-aware target triage. Also returns the fpocket pockets with both rankings (fpocket score and Druggability Score), which one selected the top pocket, and the pLDDT of the residues lining each pocket.mosaic_pathway_contextGet pathway context for a drug target. Shows which biological pathways the target participates in, other targets in the same pathways, and protein-protein interactions.mosaic_target_validationAssay precedent for a drug target: what has been tried, in what model system. Returns literature-derived experimental precedent — genetic (CRISPR/siRNA/KO), in vivo (mouse/rat/xenograft), pharmacological (inhibitor/SAR), and clinical- trial evidence — re-classified per paper at query time. A paper may carry several methods; counts are lower bounds, not exhaustive. Papers that name the target in their title are flagged high-confidence and lead the ranked exemplars. Outcomes are NOT auto-graded: open the linked exemplar papers to read what actually happened. Also returns DepMap essentiality + AlphaMissense pathogenicity when available. A target with no precedent returns an explicit no_precedent_in_corpus status (corpus coverage, not confirmed absence).mosaic_clinical_pipelineGet clinical trial pipeline for compounds targeting a gene. Returns compounds in clinical development with indications, trial phases, and status from ClinicalTrials.gov data.mosaic_synthetic_lethal_whitespaceFind synthetic-lethal *whitespace*: targets functionally coupled to a developed (drugged) target but themselves undeveloped. For an anchor target with chemical matter, surfaces partners coupled to it by DepMap co-essentiality, STRING protein-protein interactions and/or Reactome pathways. Returns TWO lists, deliberately not merged: - `candidates` — partners Mosaic covers, filtered to < 5 patents and no compound past phase 0. Those counts are measured, so a whitespace claim is supportable. Ranked by `whitespace_score`. **Read `clinical_absence_caveat`**: it is set when a partner carries substantial chemistry yet nothing clinical, which usually means our compound set is incomplete rather than that the world has no clinical interest. - `coupled_unassessed` — partners outside the curated universe. They are coupled to the anchor, but their competitive status is UNKNOWN rather than zero, so they carry null counts and no whitespace_score, and are ranked by `coupling_strength` alone. Leads, not evidence. Do not describe them as uncontested. Scope: DepMap co-essentiality IS ingested, but most rows do not use it. `co_functionality_basis` is one of `depmap_coessentiality` (measured co-essentiality), `ppi_pathway_proxy` (protein interaction AND a shared pathway), `ppi_only` (protein interaction alone, pathways checked and none shared — the weakest, and on a KRAS anchor the most common), or `ppi_pathways_unassessed` (interaction only, and pathways COULD NOT be checked because the partner is outside the curated universe — those rows also carry `shared_pathways: null`, not 0). `basis_note` gives the split. A proxy row is a hypothesis about functional coupling, not measured synthetic lethality. `sufficient_for_absence_claim` is false unless most of the coupled set was assessable; `assessed_fraction` reports how much was. `lineage` is still a label only — it does not filter. Hypothesis generator.mosaic_resistance_bypass_mapCandidate resistance-bypass / escape targets for a given target. From a deterministic keyword pass over the literature (resistance_relations — GLiREL has no resistance edge type), surfaces targets co-mentioned with the query target in resistance-context abstracts, ranked by a drugability-gap score (strong resistance evidence, low development activity). Hypothesis generator, not evidence — every row carries its source snippet.mosaic_target_networkGet the 1-hop neighborhood around a drug target. Returns the entities DIRECTLY connected to the target — compounds, diseases, pathways, patent-holding organizations, interacting proteins — as nodes and edges. This is a star centered on the target (independent 1-hop lookups), not a multi-hop graph traversal: it shows the target's immediate context, not paths that hop through intermediate entities.
Taiwan Health MCP tools 59
health_checkReturn runtime readiness of the MCP server and every module-backed service. Call this first before any workflow to confirm the required services are online.calculate_chads2_vascCHA₂DS₂-VASc stroke-risk score for non-valvular atrial fibrillation (0–9). Accepts raw age/sex and computes brackets internally; also returns the 2024 ESC CHA₂DS₂-VA adjusted score (sex removed). Decision support only.calculate_wells_peWells criteria for pulmonary embolism (two-tier + three-tier risk). Binary findings are booleans; heart_rate_bpm is raw and the >100 criterion is computed.calculate_wells_dvtWells criteria for deep-vein thrombosis (two-tier + three-tier risk). All items are binary clinical findings.calculate_das28DAS28 rheumatoid arthritis disease activity. formula=esr needs esr (mm/h); formula=crp needs crp (mg/L). Joint counts are 28-joint (0–28); global_health is a 0–100 VAS (not the 0–10 scale CDAI uses). Returns score and activity band (remission/low/moderate/high).calculate_cdaiCDAI (lab-free) rheumatoid arthritis disease activity (0–76). Tender and swollen counts use the 28-joint assessment (0–28 each); patient and provider global assessments are 0–10.calculate_bmiBody mass index with Taiwan (Asian) cutoffs: <18.5 underweight, 18.5–23.9 normal, 24–26.9 overweight, ≥27 obese. Height in cm (not metres), weight in kg.calculate_egfrEstimated glomerular filtration rate using the CKD-EPI 2021 creatinine equation (race-free), adults ≥18 only. serum_creatinine_mgdl in mg/dL (convert µmol/L by dividing by 88.4). Returns eGFR in mL/min/1.73m² and KDIGO CKD stage.calculate_has_bledHAS-BLED bleeding risk on oral anticoagulation (0–9). Accepts raw age (the >65 criterion is computed) and raw systolic BP (the H criterion is computed as SBP >160 mmHg). Returns score and high/low bleeding-risk category (≥3 high).calculate_curb65CURB-65 community-acquired pneumonia severity (0–5). BUN in mg/dL (threshold >19), respiratory rate ≥30, hypotension SBP<90 or DBP≤60, confusion, age ≥65.calculate_qsofaqSOFA sepsis screening (0–3): respiratory rate ≥22, altered mentation (GCS <15), systolic BP ≤100. ≥2 suggests sepsis and further evaluation.calculate_gcsGlasgow Coma Scale (3–15). eye_response 1–4, verbal_response 1–5, motor_response 1–6. Returns total, E/V/M sub-scores, and mild/moderate/severe severity (≤8 severe).- +47 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Mosaic Pre Clinical Intelligence
{
"mcpServers": {
"mosaic-pre-clinical-intelligence-2": {
"command": "uvx",
"args": [
"mosaic-mcp"
],
"env": {
"DATABASE_URL": "YOUR_DATABASE_URL_HERE",
"MOSAIC_API_KEY": "YOUR_MOSAIC_API_KEY_HERE",
"MOSAIC_TIER": "YOUR_MOSAIC_TIER_HERE"
}
}
}
}
Taiwan Health MCP
No confirmed install command for Taiwan Health MCP yet — follow the setup steps linked from its listing page rather than a guessed package name.
Frequently asked questions
Mosaic Pre Clinical Intelligence is categorized under Biology & Bioinformatics and uses a local stdio subprocess. Taiwan Health MCP belongs to Biology & Bioinformatics and uses an install path we have not confirmed yet. Pick Mosaic Pre Clinical Intelligence for biology & bioinformatics work and Taiwan Health MCP for biology & bioinformatics.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Taiwan Health MCP has no confirmed install command yet — follow its own setup instructions.
Mosaic Pre Clinical Intelligence has no declared pricing — check the project's own site. Taiwan Health MCP is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add mosaic-pre-clinical-intelligence-2 and taiwan-health-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Mosaic Pre Clinical Intelligence has a quality signal of 57/100 (Good) with 3 views, 0 installs and 0 GitHub stars. Taiwan Health MCP has 60/100 (Good) with 1 views, 0 installs and 167 GitHub stars.