Scite MCP Server

https://api.scite.ai/mcp Remote v1.0.0

Published by api.scite.ai — no publish provenance and no public repository, so the publisher could not be verified and the source cannot be independently located.

Ground answers in scientific literature. Search full text, evaluate trust, access full-text articles

Trust grade
A
97/100
Last scanned get badge →
Trust
A · 97/100
Adoption risk for you: the threat score, then adjusted down for blast radius, publisher verification and how much the scan could see. Deterministic; every point is auditable.
Capability
Moderate
Blast radius if it went rogue — what the server’s tools could reach. Independent of trust.
Coverage
Live
How much the scan could actually inspect. Shallow coverage is stated, never hidden.
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A Why this grade threat 100 − adoption risk = 97/100

The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.

1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:

The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.

2. Client adoption risk — 100 − 3 = 97. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:

PointsAdoption-risk factor
−3 capability blast radius (moderate) — client exposure if the model is manipulated

Capability observations and info notes are shown under Findings but never scored. Open any row's finding below for the file, line and evidence behind a deduction.

Findings 0

✓ No findings. The scan raised nothing on this surface — see Coverage for how deep it could look.

Tools 25

Each tool and what it can reach — enumerated from the running server.

  • get_510k_summaryingests untrusted input
  • get_clinical_trialingests untrusted input
  • get_collectioningests untrusted input
  • get_device510kingests untrusted input
  • get_drugingests untrusted input
  • get_faers_reportingests untrusted input
  • get_grantingests untrusted input
  • get_maude_reportingests untrusted input
  • get_mhra_alertingests untrusted input
  • add_dois_to_collectionno sensitive capability
Show 15 more tools ↓
  • create_collectionno sensitive capability
  • delete_collectionno sensitive capability
  • remove_dois_from_collectionno sensitive capability
  • search_510k_summariesno sensitive capability
  • search_clinical_trialsno sensitive capability
  • search_collectionsno sensitive capability
  • search_device510kno sensitive capability
  • search_drugsno sensitive capability
  • search_faersno sensitive capability
  • search_grantsno sensitive capability
  • search_literatureno sensitive capability
  • search_maudeno sensitive capability
  • search_mhrano sensitive capability
  • search_patentsno sensitive capability
  • update_collectionno sensitive capability

Versions 1

Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.

VersionScoreFindingsEngineScanned
v1.0.0 latest A 97/100 0 1.10.0 2026-07-25

Embed this score

Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.

MCP Trust Score: A · 97/100
Markdown (GitHub README)
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Verify this score yourself

The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.

npx mcptrustchecker scan https://api.scite.ai/mcp --online

Use the free API → How scoring works

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