MCP server

Constat MCP — FDA Device Evidence Lifecycle

com.healthai/radar

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

FDA and CMS evidence for AI medical devices: 510(k), postmarket, reimbursement, and compliance.

Website Source

At a glance

Type

MCP server

Publisher

healthai.com (verified by the MCP Registry)

Status

Working at last check

Tools

14

Token cost

About 3,523 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http radar https://constat.dev/api/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.radar]
url = "https://constat.dev/api/mcp"

Gemini CLI

{"mcpServers":{"radar":{"httpUrl":"https://constat.dev/api/mcp"}}}

Cursor

{"mcpServers":{"radar":{"url":"https://constat.dev/api/mcp"}}}

VS Code

{"servers":{"radar":{"type":"http","url":"https://constat.dev/api/mcp"}}}

Antigravity

agy mcp add radar https://constat.dev/api/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"radar","server_url":"https://constat.dev/api/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"radar","server_url":"https://constat.dev/api/mcp"}

Tools

• cohort_postmarket_stats ~152 tokens
  Postmarket presence rates across the snapshotted AI/ML device cohort (optionally by panel): share with any recall in 24 months, with a rising MAUDE trend, with any drift signal, with a warning-letter match — every rate with its denominator inline, never pooled across devices.
• device_evidence_lookup ~182 tokens
  Look up the structured premarket evidence FDA accepted for a specific AI/ML-enabled device by 510(k) number (e.g. K252148). Returns parsed summary fields — validation study design, sample sizes, endpoints, reported performance, predicate chain, PCCP — each with a verbatim source quote and page. Null
• device_postmarket_lookup ~201 tokens
  Post-clearance intelligence for one AI/ML device by 510(k) number: its product code's recalls, MAUDE adverse-event level and trend, warning-letter and 483 matches for the applicant, plus per-device drift signals (adverse-event inflection, re-clearances of the same device line, software-recall patter
• device_risk_lookup ~168 tokens
  Review a medical-device category's public FDA signals by three-letter product code (e.g. FRN = infusion pump). Returns recalls, MAUDE adverse-event trend, warning-letter matches, a normalized category signal, its driver contributions, and interpretation limits. It does not predict enforcement agains
• evidence_cohort_stats ~202 tokens
  Reporting-rate stats across the parsed AI/ML corpus (optionally by panel). Each rate is a presence figure with its denominator — 'reported in X of Y audited devices' — never a pooled performance value. Excludes not-yet-parsed devices from every denominator and discloses the parse queue separately. P
• evidence_search ~415 tokens
  Find AI/ML device clearances by filter — product code, panel, applicant, and whether the submission reported clinical data, any sensitivity metric, or a PCCP. Answers 'what evidence did FDA accept for devices like mine'. Returns bounded discovery summaries; call device_evidence_lookup with a result'
• firm_compliance_history ~393 tokens
  Build a recent, source-bounded FDA public-record timeline for a device firm: matched recalls, warning letters, and Form 483 citations where exact FEI numbers are available. Product codes are discovered from Constat's AI/ML-device corpus or may be supplied explicitly. Returns attribution and coverage
• postmarket_search ~406 tokens
  Find AI/ML devices by postmarket criteria — product code, panel, applicant, whether any drift signal exists, minimum recalls in 24 months, or a rising MAUDE trend. Returns per-device postmarket summaries with drift-signal counts.
• predicate_chain ~168 tokens
  Trace the predicate ancestry of a 510(k) device, with each cited predicate's age (how many years old the predicate was when the child cleared). Reveals how AI/ML devices chain to older predicates.
• reimbursement_lookup ~272 tokens
  Trace the clearance-to-payment pathway for an AI/ML device by FDA clearance number (K/DEN, e.g. DEN170073) OR bare CPT code (e.g. 75580). Returns every payment mechanism (NTAP add-on, Category I/III CPT + CMS rate, HCPCS, MAC LCD) with amounts, effective dates, and source links, plus any commercial/
• reimbursement_search ~340 tokens
  Find AI/ML device payment pathways by mechanism — e.g. 'devices that got NTAP', 'devices paid under a Category I CPT code', 'pathways with a known CMS dollar rate'. Filters: mechanism, CPT category, NTAP status, applicant. Returns pathways with amounts, effective dates, and sources. Use reimbursemen
• reimbursement_stats ~149 tokens
  Distribution of payment mechanisms across the AI/ML reimbursement corpus — pathway and distinct-device counts per mechanism (NTAP, Cat I, Cat III/APC, …) with the min/median/max dollar amounts for each. Deliberately never a single pooled 'reimbursement rate': NTAP add-on amounts and CMS rates are di
• vehicle_risk_lookup ~171 tokens
  Look up NHTSA safety history for a vehicle by make, model, and model year. Returns recall campaigns and complaint statistics (crashes, fires, injuries, top components).
• watchlist_diff ~304 tokens
  Return machine-generated FDA public-record changes detected for monitored product codes since a caller-supplied date, plus each code's latest category snapshot and postmarket coverage. Defaults to Constat Radar's five-code watchlist and the last seven days. Analyst verdict text and internal review s

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