Skip to content
verify mcp Beta VerifyMCP is currently in beta. If you notice any issues, get in touch and we’ll put it right.

Cure Cancer With AI

REMOTE · WWW.CURECANCERWITHAI.COM · SCANNED SEP 20

Free oncology data (research, trials, FDA approvals, news) plus IBM MAMMAL biomedical predictions.

0 this week 79 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →

Endpoint Security57
Transport & Reachability100
Schema Quality & AI Usability78
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 1697 tokens (~113/item across 15 items; 15 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
  • No destabilizing schema changes in the last 30 days.Pass
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 15 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 16 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

How do I install the Cure Cancer With AI MCP server?

Cure Cancer With AI is a hosted endpoint at https://www.curecancerwithai.com/api/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

remote · www.curecancerwithai.com

# add to Claude Code
claude mcp add --transport http hifarrer-cure-cancer-with-ai 'https://www.curecancerwithai.com/api/mcp'
// .cursor/mcp.json
{
  "mcpServers": {
    "hifarrer-cure-cancer-with-ai": {
      "url": "https://www.curecancerwithai.com/api/mcp"
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "hifarrer-cure-cancer-with-ai": {
      "type": "http",
      "url": "https://www.curecancerwithai.com/api/mcp"
    }
  }
}
# ~/.codex/config.toml
[mcp_servers.hifarrer-cure-cancer-with-ai]
url = "https://www.curecancerwithai.com/api/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "hifarrer-cure-cancer-with-ai": {
      "type": "remote",
      "url": "https://www.curecancerwithai.com/api/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add hifarrer-cure-cancer-with-ai --url 'https://www.curecancerwithai.com/api/mcp' --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  hifarrer-cure-cancer-with-ai:
    url: "https://www.curecancerwithai.com/api/mcp"
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "hifarrer-cure-cancer-with-ai": {
      "Transport": "http",
      "Url": "https://www.curecancerwithai.com/api/mcp"
    }
  }
}
# add to Vellum
assistant mcp add hifarrer-cure-cancer-with-ai -t streamable-http -u 'https://www.curecancerwithai.com/api/mcp'
// mcp.json
{
  "mcpServers": {
    "hifarrer-cure-cancer-with-ai": {
      "type": "http",
      "url": "https://www.curecancerwithai.com/api/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 26 Aug 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 25 Aug 26 0
    • Stability: 0.97 → pass security
  • 24 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

  • 11 Aug 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 31 Jul 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 27 Jul 26 0
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 26 Jul 26 0

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 20 Sept 2026 · Probed https://www.curecancerwithai.com/api/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=www.curecancerwithai.com CN=YE2,O=Let's Encrypt,C=US 26 Jul 2026 24 Oct 2026 ECDSA 256 ECDSA-SHA384 5cacda3bcdaf76f4586c24d8d36c5ebd0d3
SANs: www.curecancerwithai.com
CN=YE2,O=Let's Encrypt,C=US (CA) CN=Root YE,O=ISRG,C=US 3 Sept 2025 2 Sept 2028 ECDSA 384 ECDSA-SHA384 4df3b15dd6c0784c507cd37b58e6f115
CN=Root YE,O=ISRG,C=US (CA) CN=ISRG Root X2,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 ECDSA-SHA384 872165fc34b6e5fba8add5b3705fb53a
CN=ISRG Root X2,O=Internet Security Research Group,C=US (CA) CN=ISRG Root X1,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 SHA256-RSA 6c8f1dc727c7117f7baf853ac980f9cd

Background: What to check on a remote MCP endpoint →

DNSSEC insecure

Validation of www.curecancerwithai.com. Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
com. present 19718 13 Verified
curecancerwithai.com. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200

Background: How OAuth 2.1 works in the 2026 MCP spec →

Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://www.curecancerwithai.com/api/mcp Verified 200
http (plaintext) http://www.curecancerwithai.com/api/mcp HTTPS enforced 301 https://www.curecancerwithai.com/api/mcp
MCP tools · 15 exposed · ~1,605 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
get_blog_post ~44

Fetch a single blog post by slug, including the full article content.

NameTypeReqDescription
slugstringyesBlog post slug, e.g. "immunotherapy-breakthroughs".

No output schema declared.

No examples provided.

get_clinical_trial ~56

Fetch a single clinical trial by NCT id (or internal id), including eligibility criteria and locations.

NameTypeReqDescription
nctIdstringyesNCT id or internal id, e.g. "NCT01234567".

No output schema declared.

No examples provided.

get_research_paper ~50

Fetch a single research paper by its internal id or PubMed id.

NameTypeReqDescription
idOrPubmedIdstringyesInternal id or PubMed id, e.g. "38123456".

No output schema declared.

No examples provided.

list_blog_posts ~110

List editorial blog articles (excerpts). Use get_blog_post for full content. Filter by category, cancer-type tag, or keyword.

NameTypeReqDescription
cancerTypestringFilter by cancer-type tag.
categorystringFilter by primary category.
limitintegerResults per page (1–100, default 20).
offsetintegerNumber of results to skip (default 0).
searchstringKeyword search across title, excerpt, and content.

No output schema declared.

No examples provided.

list_clinical_trials ~119

List clinical trials from public registries (conditions, status, intervention type). Filter by condition, status (e.g. RECRUITING), or keyword.

NameTypeReqDescription
conditionstringFilter by condition.
limitintegerResults per page (1–100, default 20).
offsetintegerNumber of results to skip (default 0).
searchstringKeyword search across title and description.
statusstringFilter by trial status, e.g. RECRUITING.

No output schema declared.

No examples provided.

list_compound_characteristics ~41

List the pharmaceutical-compound characteristics (each scored on the −4…+4 scale) that can be used as preference keys in search_compounds.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

list_fda_approvals ~165

List FDA-approved oncology drugs with indication, company, approval date, and label links. Filter by cancer type, keyword, or approval date.

NameTypeReqDescription
cancerTypestringFilter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.
fromstringISO date lower bound (e.g. 2024-01-01).
limitintegerResults per page (1–100, default 20).
offsetintegerNumber of results to skip (default 0).
searchstringKeyword search across drug name, generic name, and indication.
tostringISO date upper bound (e.g. 2024-12-31).

No output schema declared.

No examples provided.

list_news ~152

List curated cancer news articles aggregated from trusted sources. Filter by cancer type, keyword, or published date.

NameTypeReqDescription
cancerTypestringFilter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.
fromstringISO date lower bound (e.g. 2024-01-01).
limitintegerResults per page (1–100, default 20).
offsetintegerNumber of results to skip (default 0).
searchstringKeyword search across title, summary, and content.
tostringISO date upper bound (e.g. 2024-12-31).

No output schema declared.

No examples provided.

list_research ~178

List peer-reviewed oncology research papers ingested from PubMed (abstracts, authors, journal, plain-language summaries). Filter by cancer type, treatment type, keyword, or publication date.

NameTypeReqDescription
cancerTypestringFilter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.
fromstringISO date lower bound (e.g. 2024-01-01).
limitintegerResults per page (1–100, default 20).
offsetintegerNumber of results to skip (default 0).
searchstringKeyword search across title and abstract.
tostringISO date upper bound (e.g. 2024-12-31).
treatmentTypestringFilter by treatment type.

No output schema declared.

No examples provided.

mammal_health ~42

Check whether the IBM MAMMAL prediction model is loaded and ready. No API key required. Call this before predict_* tools if a prior prediction timed out.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

predict_clintox ~77

Predict clinical-trial toxicity for a compound using IBM MAMMAL. Returns pred 1 (toxic / likely to fail trials) or 0 (not toxic) plus a raw score. Inference is CPU-bound and may take up to ~60s.

NameTypeReqDescription
smilesstringyesCompound structure in SMILES notation.

No output schema declared.

No examples provided.

predict_dti ~111

Predict drug–target binding affinity as pKd (−log10 Kd; higher = stronger binding) using IBM MAMMAL. Inference is CPU-bound and may take up to ~60s.

NameTypeReqDescription
drug_seqstringyesDrug structure in SMILES notation.
norm_y_meannumberOptional normalization mean override.
norm_y_stdnumberOptional normalization standard-deviation override.
target_seqstringyesTarget protein amino-acid sequence (single-letter codes).

No output schema declared.

No examples provided.

predict_ppi ~113

Predict the binding-affinity class for a pair of proteins using the IBM MAMMAL biomedical foundation model. Returns label "1" (interacting) or "0" (non-interacting). Inference is CPU-bound and may take up to ~60s.

NameTypeReqDescription
protein_astringyesAmino-acid sequence, single-letter codes (ACDEFGHIKLMNPQRSTVWY), no FASTA header.
protein_bstringyesAmino-acid sequence, single-letter codes.

No output schema declared.

No examples provided.

search_compounds ~184

Find pharmaceutical compounds two ways: by example drugs you already know (fuzzy-matched), or by setting target characteristics on a −4…+4 scale. Provide exactly one of `examples` or `preferences`. Use list_compound_characteristics for the available preference names.

NameTypeReqDescription
examplesarrayKnown drug names to find similar compounds for, e.g. ["aspirin","ibuprofen"]. Mutually exclusive with preferences.
include_characteristicsbooleanInclude each result’s characteristic scores in the response.
limitintegerMax results (1–100, default 20).
preferencesobjectMap of characteristic name to desired value on the −4…+4 scale, e.g. {"Neuroactive":3,"Immunoactive":-2}. Omit a characteristic to ignore it. Mutually exclusive with examples.

No output schema declared.

No examples provided.

search_oncology ~163

Search a keyword across every Cure Cancer With AI dataset at once — research papers, news, blog posts, FDA approvals, and clinical trials — with results grouped by type. Use this first for broad discovery, then fetch a single record by id/slug/nctId for full detail.

NameTypeReqDescription
cancerTypestringFilter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.
limitintegerMax results per dataset (1–100, default 5).
qstringyesThe keyword to search for, e.g. "osimertinib".
typesstringOptional comma-separated datasets to narrow to: research,news,blog,fdaApprovals,clinicalTrials.

No output schema declared.

No examples provided.

Common questions

What is the Cure Cancer With AI MCP server?

Cure Cancer With AI is an MCP server listed in the public MCP registry as io.github.hifarrer/cure-cancer-with-ai. Free oncology data (research, trials, FDA approvals, news) plus IBM MAMMAL biomedical predictions. This page covers its hosted endpoint (https://www.curecancerwithai.com/api/mcp).

Is the Cure Cancer With AI MCP server safe to use?

Cure Cancer With AI scores 79 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the Cure Cancer With AI MCP server expose?

Cure Cancer With AI exposes 15 tools: search_oncology, list_research, get_research_paper, list_news, list_blog_posts, and 10 more. Their descriptions and schemas cost roughly 1,605 tokens of context every time the server is loaded.

Does the Cure Cancer With AI MCP server require authentication?

No. We connected to Cure Cancer With AI without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

Is the Cure Cancer With AI MCP server still maintained?

Cure Cancer With AI is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.