Prototyp · Vorschau: alle Server aus der offiziellen Registry, alle 30 Minuten synchronisiert. Bewertungen und Benutzerkonten folgen in einem späteren Schritt.
PopNx MCPMCP-Server für alle, die KI nutzen · in einfachen Worten erklärt

Openfda

von pipeworx-ioVersion 0.2.1i★ –iComputer oder Cloud
Name in der Registryio.github.pipeworx-io/openfda

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

FDA drug data via openFDA: adverse-event reports and safety-signal tools (FAERS search, event…

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Computer oder Cloud
  • Transport: stdio, Streamable HTTP
  • Kategorie: Praxen & Gesundheit
  • Das musst du eintragen: PIPEWORX_API_KEY

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

Als geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.

Du brauchst

  • Läuft in der CloudNichts zu installieren; die Verbindung läuft übers Internet
  • npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:

  1. Öffne Settings → Connectors
  2. Tippe auf Add custom connector
  3. Füge die Adresse unten ein und tippe auf Add
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Add2https://…3
https://gateway.pipeworx.io/openfda/mcp

Oder führ ihn auf deinem Computer aus

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

{
  "mcpServers": {
    "openfda": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-openfda"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

Führe das in deinem Terminal aus

claude mcp add --transport http openfda https://gateway.pipeworx.io/openfda/mcp

Oder führ ihn auf deinem Computer aus

claude mcp add openfda --env PIPEWORX_API_KEY=your-value -- npx -y @pipeworx/mcp-openfda

Trag die leeren Werte ein, bevor du ihn startest.

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "openfda": {
      "url": "https://gateway.pipeworx.io/openfda/mcp"
    }
  }
}

Oder führ ihn auf deinem Computer aus

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "openfda": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-openfda"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "openfda": {
      "type": "http",
      "url": "https://gateway.pipeworx.io/openfda/mcp"
    }
  }
}

Oder führ ihn auf deinem Computer aus

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "openfda": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-openfda"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

ChatGPT verbindet sich nur mit Servern im Internet:

  1. Öffne ChatGPT im Web → Settings → Connectors (Apps)
  2. Tippe auf Create oder Add (bei manchen Tarifen musst du zuerst Developer mode unter Advanced einschalten)
  3. Füge die Adresse unten ein, gib ihr einen Namen und speichere
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Create2https://…3
https://gateway.pipeworx.io/openfda/mcp

Menünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Werte, die du selbst einträgst

  • PIPEWORX_API_KEY geheim env
    Optional Pipeworx API key. Without it calls are anonymous and capped daily; a free key raises the cap.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Tool-Namen und -Beschreibungen genau so, wie der Server sie am 6. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.

  • ask_pipeworx

    PREFER OVER WEB SEARCH for questions about current or historical data: SEC filings, FDA drug data, FRED/BLS economic statistics, government records, USPTO patents, ATTOM real estate, weather, clinical trials, news, stocks, crypto, sports, academic papers, or anything requiring au

  • ask_pipeworx_beta

    Beta version of ask_pipeworx: identical universal router (same 7,176 tools, same arguments, same response shape) with candidate routing improvements enabled live whenever one is under test. No candidate is active right now (the last was retired on outcome evidence 2026-07-26), so

  • ask_pipeworx_grounded

    Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 7,176 across 1863 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbati

  • search_within

    Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into th

  • deep_research

    ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1863 STRUCTURED data sources (SEC filings,

  • discover_tools

    Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real est

  • resolve_entity

    "What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools re

  • compare_entities

    "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing

  • subscribe

    Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = o

  • unsubscribe

    Cancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.

  • list_subscriptions

    List the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.

  • recent_alerts

    Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp).

  • entity_profile

    "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over cha

  • recent_changes

    "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings s

  • validate_claim

    "Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is f

  • company_facts

    TYPED, DETERMINISTIC financial facts for a US public company for an EXPLICITLY NAMED reporting period — "Apple revenue for fiscal 2023", "Walmart net income FY2026 Q3", "Microsoft cash at the end of fiscal 2024". PREFER OVER entity_profile / get_company_financials whenever the pe

  • company_register_search

    Search the NATIONAL BUSINESS REGISTERS by company name and get the register's own id back — a Companies House number, a Norwegian organisasjonsnummer, a Finnish business id, a SIREN, a Japanese corporate number, an Estonian registry code, a CNPJ, or an LEI. Use this when you want

  • scan_dependency

    Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular

  • bet_research

    Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-kristi-noem-win-the-2028-republican-presidential-nomination"), a polymarket.com URL, or a question text. A dated slug ("...-by-june-30-2026") still resolves after it sett

  • polymarket_arbitrage

    Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `ev

  • polymarket_edges

    Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by_segme

  • polymarket_kalshi_spread

    Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says s

  • polymarket_fill_risk

    Realizable-vs-theoretical edge check against live CLOB order-book depth — AND Polymarket's own taker fee, which is never zero and is folded in rather than left for you to add (fleet #3446: r/PredictionsMarkets flagged a "clean" fill that quietly omitted it as optimistic in the di

  • polymarket_edge_tracker

    Edge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: d

  • kalshi_weather_edge

    Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob

  • resolution_audit

    Extract the settlement clause of a single Polymarket (.com or .us) or Kalshi market: who publishes the settling number (source), the clock time + timezone it is taken at (falling back to the market TITLE when the clause itself says "the time range specified in the title" — e.g. P

  • resolution_diff

    Field-by-field diff of TWO markets' settlement clauses (one from each of `a` and `b`; either can be Polymarket .com, Polymarket US, or Kalshi) — runs resolution_audit on both sides and compares source, settle time, precision, comparison_basis, and evidence standard. Returns `equi

  • release_calendar_markets

    JOIN of the official release calendar (econ data, the FOMC, FDA decisions, SEC rules) against LIVE Polymarket/Kalshi markets — which scheduled releases land in the next N hours, and which live markets resolve on them. This is a POSITIONING tool, not a speed product: results are c

  • prediction_calibration

    REALIZED win rate by shown price and minutes elapsed for short-horizon crypto up/down markets, net of taker fee — read from our own settled-outcomes archive, not from live prices. Answers the one question no venue will: "a side shown at 82 with five minutes left, how often did it

  • updown_venue_compare

    The same 15-minute crypto "up or down" window priced on polymarket.com, Polymarket US and Kalshi, side by side, with whether each pair is actually the same contract. Pass asset (btc | eth | sol | xrp | bnb) and window ("current" default, "next", "previous", or the window START as

  • updown_divergence_rate

    How often two venues settled the SAME 15-minute crypto window differently, over every settled window on record. Compares polymarket.com (Chainlink TWAP) with Kalshi and with Polymarket US (both CF Benchmarks BRTI), and Kalshi with Polymarket US as the same-feed control. Per pair:

  • archive_evidence

    What did a web page say on a given date? Finds the archived capture of a URL nearest that date across the Internet Archive Wayback Machine, Common Crawl and Arquivo.pt, reads it, and returns the readable text (HTML stripped) with the capture timestamp, a link to the archived copy

  • archive_compare

    What changed on a web page between two dates? Resolves the archived capture nearest each date (Internet Archive Wayback Machine, Common Crawl, Arquivo.pt), extracts the readable text of both, and returns a text-level diff: the segments removed and added, a similarity score, and b

  • research_row

    Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code in

  • classify_row

    Cheap categorization: given a company and a list of candidate labels, decide which labels apply — the most common GTM/AI usage shape (tagging a list by industry, ICP fit, etc.), one small model call. Same evidence contract as research_row: each label comes back {label, applies, e

  • pipeworx_trending

    What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice

  • suggest_questions

    What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed e

  • generate_llms_txt

    Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at si

  • ai_visibility_check

    Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns pe

  • scan_competitor_ai_presence

    Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our co

  • pipeworx_feedback

    Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipewor

  • remember

    Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-v

  • recall

    Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous

  • forget

    Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

  • fda_drug_events

    Search FAERS adverse event reports by drug name, MedDRA reaction term, or date range. Returns report counts, reaction types, seriousness levels, and dates. Natural multi-word reaction phrasing is retried against MedDRA preferred-term word order before an empty result is reported.

  • fda_drug_approvals

    Find FDA-approved drugs by brand name, active ingredient, or application number. To find generic versions of a drug, search by active ingredient using products.active_ingredients.name (NOT openfda.generic_name — that field only works in the label endpoint). IMPORTANT: drug names

  • fda_applications_by_cik

    Find ALL Drugs@FDA applications for a company by SEC CIK, ticker, or company name — without needing to know its FDA sponsor_name spelling. Drugs@FDA has no company-ID field: sponsor_name is free text, and one company routinely files under several forms (e.g. Eli Lilly appears as

  • fda_novel_approvals

    Most recent NOVEL drug approvals, in FDA/CDER's own sense of the word: a new drug or biologic never before approved or marketed in the U.S. (read live from FDA's own published Novel Drug Approvals list). Use for "what is the most recent novel drug the FDA approved", "how many nov

  • fda_drug_labels

    Get FDA drug labeling (SPL) by drug name OR by INDICATION. This is the tool for "what drugs are approved to treat " — it searches the indications_and_usage text, which the drugsfda approvals endpoint does NOT carry. Query by brand/generic name (openfda.brand_name:"HUMIRA"), or by

  • fda_drug_recalls

    Search FDA drug recalls and enforcement actions by drug name or reason — returns recall classification, date, reason and enforcement status. A multi-word search is tried as ALL terms first and falls back to ANY term when nothing matches all of them; the response says which happen

  • fda_drug_shortages

    Search the FDA Drug Shortages database by generic or brand name, manufacturer, status, or an advanced openFDA query. Returns national supply records and available FDA dates; reason and other details are sparse in the upstream data. This is not local pharmacy inventory or medical

  • fda_shortage_changes

    FDA drug-shortage records ordered by update_date, newest first, then restricted to the requested look-back window. Use for recently updated, discontinued, or resolved national shortages; this does not imply availability at any specific pharmacy or hospital. Most rows in any windo

  • fda_complete_response_letters

    Search FDA-disclosed Complete Response Letters for drug and biologic applications. Defaults to letter_type "COMPLETE RESPONSE"; optionally include other letter types in the same dataset. Returns the application’s current approval_status, letter metadata, an excerpt, and the offic

  • fda_crl_detail

    Retrieve one FDA Complete Response Letter by application number and optionally letter date. Returns the FDA-disclosed letter text and document URL. Confidential commercial and trade-secret material may be redacted by FDA.

  • fda_food_recalls

    Search FDA FOOD recall / enforcement reports (openFDA /food/enforcement) — product recalls, reasons, classification, recalling firm, distribution, and status. Use for food-safety / recall-history questions (distinct from fda_drug_recalls which covers drugs).

  • fda_event_counts

    Aggregate adverse events by reaction type, patient age, or outcome. Returns top reactions for a drug and event trends over time.

  • fda_warning_letters

    Search FDA WARNING LETTERS — official enforcement letters FDA sends firms for violations (CGMP, adulterated/misbranded products, unapproved claims). Answers "has received an FDA warning letter", "recent FDA warning letters about supplements/devices". By default `search` matches t

  • fda_faers_signal_summary

    Calculate report-level FAERS disproportionality routing metrics for one drug/reaction pair using a 2×2 reporting table. The reaction argument matches one whole MedDRA preferred term, so a broad word like "neuropathy" counts only reports filed under that exact term and not the spe

  • fda_faers_reaction_profile

    Summarize the most frequently co-reported FAERS reactions plus serious/non-serious report counts for a drug. Counts are spontaneous reports with duplicates, co-medications, and reporting bias—not event rates or proof of causation.

  • fda_faers_trend

    Aggregate daily FAERS report counts into calendar months for a drug and optional reaction over a bounded date window. The reaction argument matches one whole MedDRA preferred term, so a broad word like "neuropathy" counts only reports filed under that exact term and not the speci

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto pipeworx-io bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • ✓ Bestanden

    Endpunkt antwortet

    Antwort in 541 ms (HTTP 200)

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Keine Anmeldung nötig

  • ✓ Bestanden

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Wir haben 60 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden

Im Vergleich mit anderen in Praxen & Gesundheiti

  • Mehr Sterne als 0 % der anderen 866 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 89 % der anderen 866 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 866 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Openfda sicher?

Er hat 3 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Das musst du eintragen: PIPEWORX_API_KEY

Läuft er auf meinem Computer oder in der Cloud?

Beides geht: Installiere ihn auf deinem Computer oder verbinde dich mit der Cloud-Version.

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.2.1) kam vor 3 Tagen in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Mirobody, FHIR MCP Server, Google Health MCP

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Mirobody

von thetahealth

Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.

Läuft auf deinem Computer★ 1.408Apache-2.0Aktualisiert vor 5 Tagen
Installieren

MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications

Läuft auf deinem Computer★ 137Apache-2.0Aktualisiert vor 9 Tagen
Installieren

Google Health MCP

von davidmosiah

Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents

Läuft auf deinem Computer★ 79MITAktualisiert vor 4 Monaten
Installieren

README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

OpenFDA — FDA Drug, Device, and Food Data

The U.S. Food and Drug Administration's open data platform. This pack covers the drug side: adverse-event reports and safety-signal tools (FAERS search, event counts, disproportionality/ROR-PRR, reaction profiles, trends), drug and novel-drug approvals (Drugs@FDA, by-company application history), drug labels, drug and food recalls, drug shortages and shortage changes, complete response letters, warning letters, and a cross-source postmarket risk-profile compound. The official source for what's been reported to or by the FDA. Free, no auth required (rate-limited).

Part of Pipeworx — an MCP gateway connecting AI agents to 1867+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.

Why this matters for AI agents

Drug-safety questions resolve here. Adverse event volumes, label changes, approval timelines, recall posture — all structured. For the full drug picture, pair with RxNorm (canonical IDs) and ClinicalTrials.gov (trials).

Common flows:

  • Adverse events for a drug. "Reports for Ozempic" → fda_drug_events({query: "ozempic"}) → individual safety reports + counts.
  • Bucket reactions. "Top reactions reported for Ozempic" → fda_event_counts({query: "ozempic", count_field: "patient.reaction.reactionmeddrapt.exact"}) → MedDRA-coded counts.
  • Approval history. "When was Ozempic approved and for what?" → fda_drug_approvals({query: "ozempic"}).
  • Recalls. "Any Ozempic recalls?" → fda_drug_recalls({query: "ozempic"}).
  • Label content. "What does the FDA label say about contraindications?" → fda_drug_labels({query: "ozempic"}).
  • All applications for a company. "Every Drugs@FDA application Eli Lilly has filed" → fda_applications_by_cik({cik_or_ticker: "LLY"}). Resolves the company via SEC and aggregates across every sponsor_name spelling it filed under — see the pitfall below before reaching for fda_drug_approvals with a guessed sponsor name.

Used by the pharma_drug_profile and pharma_safety_report compounds.

Auth

Public, no key required. Anonymous limit is ~240 requests/min and 1,000/day, counted per IP — so every caller sharing an egress address shares one 1,000/day budget, not one each.

api.fda.gov runs on api-umbrella, the same stack as api.data.gov, so an api.data.gov key authenticates it and lifts the daily limit to 120,000. Pipeworx injects a platform key (PLATFORM_DATAGOV_KEY); bring your own with _apiKey and your calls draw on your quota instead. Register free at https://open.fda.gov/apis/authentication/.

A key that is rejected or revoked does not fail the call — the pack retries once anonymously, since openFDA is fully usable without one.

Datasets

DatasetEndpoint familyCoverage
Drug adverse events (FAERS)fda_drug_events1968-present, ~20M+ reports
Drug approvalsfda_drug_approvals1939-present (NDA/BLA/ANDA)
Drug labelsfda_drug_labelsCurrent SPL labels
Drug recallsfda_drug_recallsClass I/II/III enforcement actions
Device adverse events(separate tools)MAUDE database
Food recalls(separate tools)FSIS + FDA recalls
Warning lettersfda_warning_letters3,680 published letters from 2021-01 on, fda.gov (not api.fda.gov), plus FDA's compliance-actions archive back to 2010 for firms with nothing in that window

Common pitfalls

  • Reports are not unique patients. A single hospitalization can produce multiple FAERS reports. The total field is reports, not adverse-event-suffering-individuals.
  • Causality not implied. A FAERS report links a drug to an event temporally; it does not prove the drug CAUSED the event. Use language carefully.
  • Brand vs generic naming. Searching "ozempic" finds Ozempic-tagged reports. Searching "semaglutide" finds reports for any semaglutide product. They can differ — the user's intent determines which to search.
  • Query syntax is FDA's, not ours. OpenFDA uses Lucene-style search with field-specific queries. Pipeworx tool descriptions show the syntax. Quotation marks matter.
  • Reaction names use MedDRA word order. Natural phrasing can differ from the preferred term stored by FDA — ISCHAEMIC OPTIC NEUROPATHY is filed as OPTIC ISCHAEMIC NEUROPATHY. Reaction-filtered tools retry two- and three-word phrases in alternate word orders and disclose the resolved term in reaction_resolved.
  • Reaction filters match one whole preferred term. They are not substring or token matches, so NEUROPATHY returns only reports filed under that exact term (~1,700) rather than every term containing the word (~117,000). This is deliberate: a disproportionality table needs one case definition, not an ad-hoc grouping. To find the terms FDA actually stores, count on patient.reaction.reactionmeddrapt.exact.
  • An unmatched term is reported, not silently zeroed. When no word order matches, tools return reaction_resolution: "not_a_meddra_preferred_term" with a hint. Treat that as "the filter missed," never as "no reports exist."
  • Warning-letter search matches the RECIPIENT by default. fda_warning_letters sits on fda.gov's solr index, which covers each letter's full body as well as the company column — so a raw full-text query answers "letters that mention X", not "letters issued to X". Those are very different claims about a named firm, and the difference was live: search: "Merck" returned exactly one letter, addressed to Elanco Animal Health, which merely names Merck in its text. search now filters on the addressed company, every row carries matched_field (company vs letter_text), and match: "fulltext" is the opt-in for body search. A recipient search with no hits returns found: false with the full-text count, so "no letters" is never confused with "we did not look".
  • The published warning-letter list is a ROLLING FIVE-YEAR WINDOW, and that used to read as "this company is clean". fda.gov's view holds 3,680 letters from 2021-01-05 to today, every center included — CDER, CFSAN, CTP, CVM and Human Foods are all present, so nothing is excluded by subject, only by AGE. Hospira's real 2017-02-14 CGMP letter returned candidates_scanned: 0 and a confident "no warning letter matches \"Hospira\" at all" (fleet #2123). When a recipient search finds nothing in that window, the tool now consults FDA's Data Dashboard compliance-actions archive, which records the same enforcement events back to at least 2010. Those rows carry firm, place, product type and the issue date but no subject line and no letter URL — FDA does not republish the text of letters this old — so every row and the response itself carry source, and archive rows are never blended into the published ones. On the success path the response still says archive_note, because a firm with one 2024 letter and ten from 2015 legitimately counts 1 here. On the miss path it says archive_checked, so "we looked in both and found nothing" is distinguishable from "the archive was unreachable".
  • Warning-letter counts over broad terms are a floor. Recipient matching pages the full-text superset up to 600 candidates. Past that the response sets scan_complete: false and a scope_note, and total_matching is a lower bound — narrow the term for an exact count.
  • Lag from event to report. FAERS reports lag the event by months — sometimes years. The "last 30 days" view is misleading; recent counts will keep growing as reports flow in.
  • `sponsor_name` has no company-ID and is EXACT-match, not full-text. fda_drug_approvals queries like search=sponsor_name:"ELI LILLY AND COMPANY" match only that literal string — Eli Lilly's real applications are split across "LILLY" (116), "ELI LILLY AND CO" (22), "ELI LILLY CO" (4), and "LILLY RES LABS" (1), and the SEC-registered name matches none of them. Use fda_applications_by_cik (CIK/ticker in, every sponsor_name form aggregated out) instead of guessing spellings.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{

"mcpServers": { "openfda": { "url": "https://gateway.pipeworx.io/openfda/mcp" } } }

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/openfda/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

{

"mcpServers": { "pipeworx": { "url": "https://gateway.pipeworx.io/mcp" } } }

Both URLs reach the same gateway and the same 1867+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

No MCP client? Call it over HTTP

curl -X POST https://gateway.pipeworx.io/v1/tools/fda_drug_events \

-H 'Content-Type: application/json' \ -d '{"query":"patient.drug.medicinalproduct:\"OZEMPIC\""}'

No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/fda_drug_events. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.

Run it from npm

@pipeworx/mcp-openfda is a local stdio bridge to the Pipeworx gateway: your MCP client starts it with npx, and it forwards every call to the same https://gateway.pipeworx.io/openfda/mcp endpoint shown above. It needs network access; there is no offline mode.

{

"mcpServers": { "openfda": { "command": "npx", "args": ["-y", "@pipeworx/mcp-openfda"] } } }

Without a key it calls anonymously, capped at 50 calls a day. A free account raises that to 200 a day: get a key at https://pipeworx.io/signup and add "env": { "PIPEWORX_API_KEY": " " } to the server entry. The key is sent as a Bearer token, the same way a hosted connection sends it, so calls are metered and billed exactly as they are there.

It lists only this pack's tools by default. Set PIPEWORX_META_TOOLS=1 to also list ask_pipeworx and the other gateway-wide tools.

Behind an HTTPS proxy: Node's built-in fetch does not read HTTPS_PROXY by default. Newer Node releases honour it when NODE_USE_ENV_PROXY=1 is set; check your Node version's documentation.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

ask_pipeworx({ question: "your question about Openfda data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT

PopNx fragen