Enhancements

.gitignore

@@ -11,4 +11,6 @@ __pycache__/
 *.pyz
 *.pywz
 *.pyzw
-*.pyzwz
+*.pyzwz
+
+chatbot.py

README.md

@@ -14,6 +14,7 @@ tags:
   - drug-information
   - calculator
   - gradio
+  - mcp-server-track
 ---
 # Pharmacist MCP Server
 

app.py

@@ -166,7 +166,7 @@ def _creatinine_conversion_gradio(value: float, from_unit: str, to_unit: str):
 @with_caching(ttl=1800)
 def search_adverse_events_mcp(drug_name: str, limit: str = "5") -> str:
     """
-    Search FAERS for adverse events related to a drug and return brief summaries.
+    Searches the FDA Adverse Event Reporting System (FAERS) database for adverse events associated with a specific drug. This tool is useful for initial investigation into a drug's safety profile by retrieving summaries of reported adverse event cases. It provides a quick overview of potential side effects reported by healthcare professionals and the public.
 
     Args:
         drug_name (str): Generic or brand name to search (case-insensitive)
@@ -184,7 +184,7 @@ def search_adverse_events_mcp(drug_name: str, limit: str = "5") -> str:
 @with_caching(ttl=3600)
 def fetch_event_details_mcp(event_id: str) -> str:
     """
-    Fetch full FAERS case details by safety-report ID.
+    Retrieves the complete details of a specific adverse event case from the FDA Adverse Event Reporting System (FAERS) using its unique safety report ID. Use this tool when you need to dive deep into a particular case found via 'search_adverse_events_mcp' to understand the full context, including patient demographics, concomitant medications, and the full narrative of the event.
 
     Args:
         event_id (str): Numeric FAERS safetyreportid string
@@ -200,7 +200,7 @@ def fetch_event_details_mcp(event_id: str) -> str:
 @with_caching(ttl=7200)
 def drug_label_warnings_mcp(drug_name: str) -> str:
     """
-    Get FDA label warnings including boxed warnings, contraindications, and drug interactions.
+    Fetches critical safety information from the official FDA drug label. This includes boxed warnings (the most serious type), contraindications (situations where the drug should not be used), and known drug interactions. This is a primary tool for assessing a drug's major safety risks before prescribing or dispensing.
 
     Args:
         drug_name (str): Generic drug name preferred
@@ -216,7 +216,7 @@ def drug_label_warnings_mcp(drug_name: str) -> str:
 @with_caching(ttl=3600)
 def drug_recalls_mcp(drug_name: str, limit: str = "5") -> str:
     """
-    Find recent FDA recall events for a drug.
+    Searches for recent FDA-issued recall events for a specific drug product. This is critical for ensuring patient safety by identifying if a drug or specific batch has been recalled due to manufacturing defects, contamination, or other safety concerns. The results include details on the recall reason, status, and affected lots.
 
     Args:
         drug_name (str): Free-text search string for the drug
@@ -234,7 +234,7 @@ def drug_recalls_mcp(drug_name: str, limit: str = "5") -> str:
 @with_caching(ttl=7200)
 def drug_pregnancy_lactation_mcp(drug_name: str) -> str:
     """
-    Get pregnancy and lactation information from FDA drug labels.
+    Retrieves specific sections from the FDA drug label related to use during pregnancy and lactation. This tool is essential for assessing the safety of a medication for patients who are pregnant, planning to become pregnant, or breastfeeding. It provides the official guidance and available data on potential risks.
 
     Args:
         drug_name (str): Generic drug name preferred
@@ -250,7 +250,7 @@ def drug_pregnancy_lactation_mcp(drug_name: str) -> str:
 @with_caching(ttl=7200)  # 2 hours cache
 def drug_dose_adjustments_mcp(drug_name: str) -> str:
     """
-    Get renal and hepatic dose adjustment information from FDA labels.
+    Extracts dosing adjustment recommendations for patients with kidney (renal) or liver (hepatic) impairment from the official FDA drug label. This is a crucial tool for safe and effective dosing in special populations where standard doses may be harmful or ineffective.
 
     Args:
         drug_name (str): Generic drug name
@@ -266,7 +266,7 @@ def drug_dose_adjustments_mcp(drug_name: str) -> str:
 @with_caching(ttl=1800)  # 30 minutes cache
 def drug_livertox_summary_mcp(drug_name: str) -> str:
     """
-    Get hepatotoxicity information from the LiverTox database.
+    Queries the NIH LiverTox database to retrieve a summary of a drug's potential for causing liver injury (hepatotoxicity). This tool is valuable for investigating or assessing the risk of drug-induced liver damage, providing information on the mechanism of injury, and clinical management advice.
 
     Args:
         drug_name (str): Drug name to search for (case-insensitive)
@@ -281,7 +281,7 @@ def drug_livertox_summary_mcp(drug_name: str) -> str:
 @with_error_handling
 def brand_to_generic_lookup_mcp(brand_name: str) -> str:
     """
-    Look up generic drug information from brand names.
+    Converts a drug brand name to its generic (active ingredient) name. It can also provide information on the countries where the brand name is marketed. This tool is fundamental for identifying the active component of a branded medication, which is necessary for most other clinical lookups and to avoid therapeutic duplication.
 
     Args:
         brand_name (str): Brand name to look up
@@ -296,11 +296,9 @@ def brand_to_generic_lookup_mcp(brand_name: str) -> str:
 @with_error_handling
 def calculate_drug_burden_index_mcp(drug_list: str) -> str:
     """
-    Calculate Drug Burden Index (DBI) from a list of medications with automatic route detection.
+    Calculates the Drug Burden Index (DBI) for a patient's medication list. The DBI is a measure of a person's total exposure to anticholinergic and sedative drugs, which are associated with an increased risk of falls and cognitive impairment, especially in the elderly. 
     
-    This intelligent version automatically detects the route of administration for each medication
-    (oral, transdermal patches, parenteral injections, etc.) and uses the appropriate reference
-    data for each route. Perfect for real-world medication lists with mixed formulations.
+    This intelligent version automatically detects the route of administration for each medication (e.g., oral, transdermal patches, parenteral injections) and uses the appropriate reference data for each route, making it suitable for complex, real-world medication regimens.
 
     Args:
         drug_list (str): Drug list (one per line, include dose and frequency - also write "prn" if the drug is a PRN medication)
@@ -324,7 +322,7 @@ def calculate_creatinine_clearance_mcp(
     age: str, weight_kg: str, serum_creatinine: str, is_female: str
 ) -> str:
     """
-    Calculate creatinine clearance using Cockcroft-Gault equation.
+    Calculates a patient's creatinine clearance (CrCl) using the Cockcroft-Gault equation. CrCl is an estimate of the glomerular filtration rate (GFR) and is widely used to determine appropriate dose adjustments for drugs that are cleared by the kidneys. This is a standard clinical calculator for renal function assessment.
 
     Args:
         age (str): Patient's age in years
@@ -351,7 +349,7 @@ def calculate_egfr_mcp(
     age: str, serum_creatinine: str, is_female: str, is_black: str
 ) -> str:
     """
-    Calculate estimated glomerular filtration rate using CKD-EPI equation.
+    Calculates the estimated Glomerular Filtration Rate (eGFR) using the CKD-EPI 2021 equation. eGFR is a key indicator of kidney function and is used to diagnose, stage, and manage Chronic Kidney Disease (CKD). This is the preferred method for assessing kidney function in many clinical guidelines.
 
     Args:
         age (str): Patient's age in years
@@ -376,7 +374,7 @@ def calculate_child_pugh_score_mcp(
     bilirubin: str, albumin: str, inr: str, ascites: str, encephalopathy: str
 ) -> str:
     """
-    Calculate Child-Pugh score for liver function assessment.
+    Calculates the Child-Pugh score, a well-established tool for assessing the prognosis of chronic liver disease, primarily cirrhosis. The score is used to determine the severity of liver disease and to guide dosage adjustments for drugs that are metabolized by the liver.
 
     Args:
         bilirubin (str): Total bilirubin in mg/dL
@@ -401,7 +399,7 @@ def calculate_child_pugh_score_mcp(
 @with_error_handling
 def calculate_bmi_mcp(weight_kg: str, height_cm: str) -> str:
     """
-    Calculate Body Mass Index (BMI) and weight category.
+    Calculates a person's Body Mass Index (BMI) based on their weight and height. BMI is a widely used screening tool to categorize weight status (e.g., underweight, normal weight, overweight, obese) and identify potential health risks associated with weight.
 
     Args:
         weight_kg (str): Weight in kilograms
@@ -420,7 +418,7 @@ def calculate_bmi_mcp(weight_kg: str, height_cm: str) -> str:
 @with_error_handling
 def calculate_ideal_body_weight_mcp(height_cm: str, is_male: str) -> str:
     """
-    Calculate Ideal Body Weight (IBW) using the Devine formula.
+    Calculates a patient's Ideal Body Weight (IBW) using the Devine formula. IBW is used in various clinical contexts, including for calculating the dose of certain medications (e.g., aminophylline, digoxin) and for assessing nutritional status.
 
     Args:
         height_cm (str): Patient's height in cm
@@ -441,7 +439,7 @@ def recommend_dosing_weight_mcp(
     actual_weight: str, height_cm: str, is_male: str
 ) -> str:
     """
-    Recommend appropriate weight for medication dosing calculations.
+    Recommends the most appropriate weight to use for medication dosing calculations (i.e., actual, ideal, or adjusted body weight) based on the patient's actual weight and height. This is crucial for obese or underweight patients, as using the wrong weight can lead to sub-therapeutic or toxic drug levels for certain medications.
 
     Args:
         actual_weight (str): Patient's actual weight in kg
@@ -462,7 +460,7 @@ def recommend_dosing_weight_mcp(
 @with_error_handling
 def convert_creatinine_units_mcp(value: str, from_unit: str, to_unit: str) -> str:
     """
-    Convert creatinine values between mg/dL and μmol/L units.
+    Converts serum creatinine values between the two standard units of measurement: milligrams per deciliter (mg/dL) and micromoles per liter (μmol/L). This is essential for interoperability, as different laboratories and clinical calculators may use different units.
 
     Args:
         value (str): The creatinine value to convert
@@ -481,7 +479,7 @@ def convert_creatinine_units_mcp(value: str, from_unit: str, to_unit: str) -> st
 @with_error_handling
 def get_cache_stats_mcp() -> str:
     """
-    Get cache statistics for monitoring and debugging.
+    Retrieves statistics about the application's internal cache. This is a debugging and monitoring tool to assess the performance and health of the MCP server, showing metrics like hit rate and cache size. It is not typically used for clinical queries.
     
     Returns:
         str: JSON string with cache hit rates, size, and other metrics
@@ -501,7 +499,7 @@ def get_cache_stats_mcp() -> str:
 @with_error_handling
 def health_check_mcp() -> str:
     """
-    Health check endpoint for monitoring MCP server status.
+    Performs a health check on the MCP server to ensure its core components are operational. This tool is used for system monitoring to verify that the server is running, the cache is working, and basic calculations can be performed. It's not intended for clinical use.
     
     Returns:
         str: JSON string with server health information
@@ -559,7 +557,8 @@ def enhanced_faers_search_mcp(
     limit: str = "100"
 ) -> str:
     """
-    Enhanced FAERS search with filtering capabilities for pharmacovigilance analysis.
+    Performs an advanced search of the FDA Adverse Event Reporting System (FAERS) database with powerful filtering options. This tool is designed for in-depth pharmacovigilance analysis, allowing users to narrow down adverse event reports by patient age, gender, and the seriousness of the event. It's ideal for identifying trends and patterns in drug safety data.
+    Use this tool particularly if the user asks about a specific adverse event or reaction.
     
     Args:
         drug_name (str): Drug name to search for
@@ -606,10 +605,20 @@ def calculate_naranjo_score_mcp(
     reaction_appeared_after_suspected_drug_given: str
 ) -> str:
     """
-    Calculate Naranjo Adverse Drug Reaction Probability Scale.
+    Calculates the Naranjo score, a standardized and widely used causality assessment tool to determine the probability that an adverse event is related to a specific drug. The score helps clinicians and researchers classify the likelihood of an adverse drug reaction (ADR) as doubtful, possible, probable, or definite.
+    Sometimes the user might not have provided all the information, so you will need to ask for the missing information (remember to give them the option to say "unknown" if they don't know the answer)
     
     Args:
-        All parameters should be "yes", "no", or "unknown"
+        adverse_reaction_after_drug (str): "yes", "no", "unknown"
+        reaction_improved_after_stopping (str): "yes", "no", "unknown"
+        reaction_reappeared_after_readministration (str): "yes", "no", "unknown"
+        alternative_causes_exist (str): "yes", "no", "unknown"
+        reaction_when_placebo_given (str): "yes", "no", "unknown"
+        drug_detected_in_blood (str): "yes", "no", "unknown"
+        reaction_worse_with_higher_dose (str): "yes", "no", "unknown"
+        similar_reaction_to_drug_before (str): "yes", "no", "unknown"
+        adverse_event_confirmed_objectively (str): "yes", "no", "unknown"
+        reaction_appeared_after_suspected_drug_given (str): "yes", "no", "unknown"
     
     Returns:
         str: JSON string with score, probability category, and detailed breakdown
@@ -637,7 +646,7 @@ def disproportionality_analysis_mcp(
     background_limit: str = "10000"
 ) -> str:
     """
-    Perform disproportionality analysis to detect potential drug-adverse event signals.
+    Performs a disproportionality analysis (also known as signal detection) on adverse event data. This statistical method compares the reporting rate of a specific drug-event combination to the reporting rate of that event for all other drugs in the database. It calculates metrics like Proportional Reporting Ratio (PRR) and Reporting Odds Ratio (ROR) to identify potential safety signals that may warrant further investigation.
     
     Args:
         drug_name (str): Drug of interest
@@ -665,7 +674,7 @@ def find_similar_cases_mcp(
     limit: str = "50"
 ) -> str:
     """
-    Find cases similar to a reference case based on patient characteristics, drugs, and adverse events.
+    Identifies and retrieves adverse event cases from the FAERS database that are similar to a given reference case. Similarity is calculated based on a combination of patient demographics (age, gender), reported reactions, and concomitant drugs. This tool is useful for contextualizing a specific case and identifying potential case series for further review.
     
     Args:
         reference_case_id (str): FAERS safety report ID to use as reference
@@ -698,7 +707,7 @@ def temporal_analysis_mcp(
     limit: str = "500"
 ) -> str:
     """
-    Analyze temporal patterns of adverse events for a drug.
+    Analyzes the temporal relationship between drug administration and the onset of adverse events. This tool provides insights into the typical time-to-onset for a specific drug-associated adverse event, which can be a critical factor in causality assessment. It helps determine if the timing of the event is consistent with the drug's known pharmacology.
     
     Args:
         drug_name (str): Drug to analyze
@@ -720,230 +729,290 @@ def temporal_analysis_mcp(
     return format_json_output(standardize_response(result, "temporal_analysis"))
 
 
-ae_search_ui = gr.Interface(
-    fn=search_adverse_events_mcp,
-    inputs=[gr.Text(label="Drug Name"), gr.Text(label="Limit", value="5")],
-    outputs=gr.JSON(label="Output"),
-    title="AE Search",
-    api_name="ae_search",
-    description="Search FAERS for adverse events.",
-)
-
-ae_details_ui = gr.Interface(
-    fn=fetch_event_details_mcp,
-    inputs=gr.Text(label="FAERS Event ID"),
-    outputs=gr.JSON(label="Output"),
-    title="AE Details",
-    api_name="ae_details",
-    description="Fetch a full FAERS case by safety-report ID.",
-)
-
-warnings_ui = gr.Interface(
-    fn=drug_label_warnings_mcp,
-    inputs=gr.Text(label="Drug Name"),
-    outputs=gr.JSON(label="Output"),
-    title="Label Warnings",
-    api_name="label_warnings",
-    description="Get FDA label warnings.",
-)
-
-recalls_ui = gr.Interface(
-    fn=drug_recalls_mcp,
-    inputs=[gr.Text(label="Drug"), gr.Text(label="Limit", value="5")],
-    outputs=gr.JSON(label="Output"),
-    title="Drug Recalls",
-    api_name="drug_recalls",
-    description="Return recent FDA recall events for a drug.",
-)
-
-pregnancy_ui = gr.Interface(
-    fn=drug_pregnancy_lactation_mcp,
-    inputs=gr.Text(label="Drug"),
-    outputs=gr.JSON(label="Output"),
-    title="Pregnancy & Lactation",
-    api_name="pregnancy_lactation",
-    description="Return Pregnancy & Lactation text from FDA label.",
-)
-
-adjustments_ui = gr.Interface(
-    fn=drug_dose_adjustments_mcp,
-    inputs=gr.Text(label="Drug"),
-    outputs=gr.JSON(label="Output"),
-    title="Dose Adjustments",
-    api_name="dose_adjustments",
-    description="Return renal & hepatic dosing excerpts from FDA label.",
-)
-
-livertox_ui = gr.Interface(
-    fn=drug_livertox_summary_mcp,
-    inputs=gr.Text(label="Drug Name"),
-    outputs=gr.JSON(label="Output"),
-    title="LiverTox Summary",
-    api_name="livertox_summary",
-    description="Get hepatotoxicity information.",
-)
-
-brand_generic_ui = gr.Interface(
-    fn=brand_to_generic_lookup_mcp,
-    inputs=[
-        gr.Text(label="Brand Name"),
-    ],
-    outputs=gr.JSON(label="Output"),
-    title="Brand to Generic",
-    api_name="brand_to_generic",
-    description="Look up generic drug information.",
-)
-
-dbi_calculator_ui = gr.Interface(
-    fn=calculate_drug_burden_index_mcp,
-    inputs=[
-        gr.Textbox(
-            label="Drug List (one per line, include dose and frequency)",
-            lines=10,
-            placeholder="e.g., Fentanyl 25mcg/hr patch daily\nAmitriptyline 25mg tablet twice daily\nMorphine 10mg injection PRN",
-        ),
-    ],
-    outputs=gr.JSON(label="DBI Calculation with Route Detection"),
-    title="DBI Calculator",
-    api_name="dbi_calculator",
-    description="Intelligent DBI calculator that automatically detects routes (oral, patches, injections, etc.) and uses appropriate reference data for each medication.",
-)
-
-
-
-cockcroft_gault_ui = gr.Interface(
-    fn=calculate_creatinine_clearance_mcp,
-    inputs=[
-        gr.Text(label="Age (years)", value="65"),
-        gr.Text(label="Weight (kg)", value="70"),
-        gr.Text(label="Serum Creatinine (mg/dL)", value="1.2"),
-        gr.Text(label="Is Female (true/false)", value="false"),
-    ],
-    outputs=gr.JSON(label="Creatinine Clearance"),
-    title="Cockcroft-Gault Calculator",
-    api_name="cockcroft_gault",
-    description="Calculate creatinine clearance using Cockcroft-Gault equation for dose adjustments.",
-)
-
-ckd_epi_ui = gr.Interface(
-    fn=calculate_egfr_mcp,
-    inputs=[
-        gr.Text(label="Age (years)", value="65"),
-        gr.Text(label="Serum Creatinine (mg/dL)", value="1.2"),
-        gr.Text(label="Is Female (true/false)", value="false"),
-        gr.Text(label="Is Black (true/false)", value="false"),
-    ],
-    outputs=gr.JSON(label="eGFR"),
-    title="CKD-EPI eGFR Calculator",
-    api_name="ckd_epi",
-    description="Calculate estimated glomerular filtration rate using CKD-EPI equation.",
-)
-
-child_pugh_ui = gr.Interface(
-    fn=calculate_child_pugh_score_mcp,
-    inputs=[
-        gr.Text(label="Total Bilirubin (mg/dL)", value="1.5"),
-        gr.Text(label="Serum Albumin (g/dL)", value="3.5"),
-        gr.Text(label="INR", value="1.3"),
-        gr.Dropdown(["none", "mild", "moderate-severe"], value="none", label="Ascites"),
-        gr.Dropdown(
-            ["none", "grade-1-2", "grade-3-4"], value="none", label="Encephalopathy"
-        ),
-    ],
-    outputs=gr.JSON(label="Child-Pugh Score"),
-    title="Child-Pugh Score Calculator",
-    api_name="child_pugh",
-    description="Calculate Child-Pugh score for liver function assessment and dose adjustments.",
-)
-
-bmi_ui = gr.Interface(
-    fn=calculate_bmi_mcp,
-    inputs=[
-        gr.Text(label="Weight (kg)", value="70"),
-        gr.Text(label="Height (cm)", value="170"),
-    ],
-    outputs=gr.JSON(label="BMI Calculation"),
-    title="BMI Calculator",
-    api_name="bmi_calculator",
-    description="Calculate Body Mass Index and weight category assessment.",
-)
-
-ideal_body_weight_ui = gr.Interface(
-    fn=calculate_ideal_body_weight_mcp,
-    inputs=[
-        gr.Text(label="Height (cm)", value="170"),
-        gr.Text(label="Is Male (true/false)", value="true"),
-    ],
-    outputs=gr.JSON(label="Ideal Body Weight Calculation"),
-    title="Ideal Body Weight (IBW) Calculator",
-    api_name="ideal_body_weight",
-    description="Calculate Ideal Body Weight using the Devine formula.",
-)
-
-dosing_weight_ui = gr.Interface(
-    fn=recommend_dosing_weight_mcp,
-    inputs=[
-        gr.Text(label="Actual Weight (kg)", value="85"),
-        gr.Text(label="Height (cm)", value="170"),
-        gr.Text(label="Is Male (true/false)", value="true"),
-    ],
-    outputs=gr.JSON(label="Dosing Weight Recommendation"),
-    title="Dosing Weight Calculator",
-    api_name="dosing_weight",
-    description="Recommend appropriate weight for medication dosing calculations.",
-)
-
-creatinine_convert_ui = gr.Interface(
-    fn=convert_creatinine_units_mcp,
-    inputs=[
-        gr.Text(label="Creatinine Value", value="1.2"),
-        gr.Dropdown(["mg_dl", "umol_l"], value="mg_dl", label="From Unit"),
-        gr.Dropdown(["mg_dl", "umol_l"], value="umol_l", label="To Unit"),
-    ],
-    outputs=gr.JSON(label="Converted Value"),
-    title="Creatinine Unit Converter",
-    api_name="creatinine_converter",
-    description="Convert creatinine values between mg/dL and μmol/L.",
-)
+with gr.Blocks(
+    theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
+    title="Pharmacist MCP",
+    analytics_enabled=False
+) as demo:
+    gr.Markdown(
+        """
+        <div style="text-align: center; padding: 20px;">
+            <h1 style="color: #0B579E;">💊 Pharmacist MCP</h1>
+            <p style="font-size: 1.1em;">
+                <strong>A suite of tools for pharmacists and clinicians.</strong>
+            </p>
+            <p>
+                Access critical drug information, perform clinical calculations, and analyze adverse drug reaction data efficiently.
+            </p>
+        </div>
+        """
+    )
 
-demo = gr.TabbedInterface(
-    [
-        ae_search_ui,
-        ae_details_ui,
-        warnings_ui,
-        recalls_ui,
-        pregnancy_ui,
-        adjustments_ui,
-        livertox_ui,
-        brand_generic_ui,
-        dbi_calculator_ui,
-        cockcroft_gault_ui,
-        ckd_epi_ui,
-        child_pugh_ui,
-        bmi_ui,
-        ideal_body_weight_ui,
-        dosing_weight_ui,
-        creatinine_convert_ui,
-    ],
-    [
-        "AE Search",
-        "AE Details",
-        "Label Warnings",
-        "Recalls",
-        "Pregnancy",
-        "Dose Adjustments",
-        "LiverTox",
-        "Brand to Generic",
-        "DBI Calculator",
-        "Creatinine CL",
-        "eGFR",
-        "Child-Pugh",
-        "BMI",
-        "IBW",
-        "Dosing Weight",
-        "Unit Converter",
-    ],
-)
+    with gr.Tabs():
+        with gr.TabItem("Drug Information & Safety"):
+            with gr.Tabs():
+                with gr.TabItem("AE Search"):
+                    gr.Interface(
+                        fn=search_adverse_events_mcp,
+                        inputs=[gr.Text(label="Drug Name"), gr.Text(label="Limit", value="5")],
+                        outputs=gr.JSON(label="Output"),
+                        title="AE Search",
+                        api_name="ae_search",
+                        description="Search FAERS for adverse events.",
+                    )
+                with gr.TabItem("AE Details"):
+                    gr.Interface(
+                        fn=fetch_event_details_mcp,
+                        inputs=gr.Text(label="FAERS Event ID"),
+                        outputs=gr.JSON(label="Output"),
+                        title="AE Details",
+                        api_name="ae_details",
+                        description="Fetch a full FAERS case by safety-report ID.",
+                    )
+                with gr.TabItem("Label Warnings"):
+                    gr.Interface(
+                        fn=drug_label_warnings_mcp,
+                        inputs=gr.Text(label="Drug Name"),
+                        outputs=gr.JSON(label="Output"),
+                        title="Label Warnings",
+                        api_name="label_warnings",
+                        description="Get FDA label warnings.",
+                    )
+                with gr.TabItem("Recalls"):
+                    gr.Interface(
+                        fn=drug_recalls_mcp,
+                        inputs=[gr.Text(label="Drug"), gr.Text(label="Limit", value="5")],
+                        outputs=gr.JSON(label="Output"),
+                        title="Drug Recalls",
+                        api_name="drug_recalls",
+                        description="Return recent FDA recall events for a drug.",
+                    )
+                with gr.TabItem("Pregnancy & Lactation"):
+                    gr.Interface(
+                        fn=drug_pregnancy_lactation_mcp,
+                        inputs=gr.Text(label="Drug"),
+                        outputs=gr.JSON(label="Output"),
+                        title="Pregnancy & Lactation",
+                        api_name="pregnancy_lactation",
+                        description="Return Pregnancy & Lactation text from FDA label.",
+                    )
+                with gr.TabItem("Dose Adjustments"):
+                    gr.Interface(
+                        fn=drug_dose_adjustments_mcp,
+                        inputs=gr.Text(label="Drug"),
+                        outputs=gr.JSON(label="Output"),
+                        title="Dose Adjustments",
+                        api_name="dose_adjustments",
+                        description="Return renal & hepatic dosing excerpts from FDA label.",
+                    )
+                with gr.TabItem("LiverTox Summary"):
+                    gr.Interface(
+                        fn=drug_livertox_summary_mcp,
+                        inputs=gr.Text(label="Drug Name"),
+                        outputs=gr.JSON(label="Output"),
+                        title="LiverTox Summary",
+                        api_name="livertox_summary",
+                        description="Get hepatotoxicity information.",
+                    )
+                with gr.TabItem("Brand to Generic"):
+                    gr.Interface(
+                        fn=brand_to_generic_lookup_mcp,
+                        inputs=[gr.Text(label="Brand Name")],
+                        outputs=gr.JSON(label="Output"),
+                        title="Brand to Generic",
+                        api_name="brand_to_generic",
+                        description="Look up generic drug information.",
+                    )
+
+        with gr.TabItem("Clinical Calculators"):
+            with gr.Tabs():
+                with gr.TabItem("DBI Calculator"):
+                    gr.Interface(
+                        fn=calculate_drug_burden_index_mcp,
+                        inputs=[
+                            gr.Textbox(
+                                label="Drug List (one per line, include dose and frequency)",
+                                lines=10,
+                                placeholder="e.g., Fentanyl 25mcg/hr patch daily\nAmitriptyline 25mg tablet twice daily\nMorphine 10mg injection PRN",
+                            ),
+                        ],
+                        outputs=gr.JSON(label="DBI Calculation with Route Detection"),
+                        title="DBI Calculator",
+                        api_name="dbi_calculator",
+                        description="Intelligent DBI calculator that automatically detects routes (oral, patches, injections, etc.) and uses appropriate reference data for each medication.",
+                    )
+                with gr.TabItem("Creatinine Clearance"):
+                    gr.Interface(
+                        fn=calculate_creatinine_clearance_mcp,
+                        inputs=[
+                            gr.Text(label="Age (years)", value="65"),
+                            gr.Text(label="Weight (kg)", value="70"),
+                            gr.Text(label="Serum Creatinine (mg/dL)", value="1.2"),
+                            gr.Radio(["true", "false"], label="Is Female", value="false"),
+                        ],
+                        outputs=gr.JSON(label="Creatinine Clearance"),
+                        title="Cockcroft-Gault Calculator",
+                        api_name="cockcroft_gault",
+                        description="Calculate creatinine clearance using Cockcroft-Gault equation for dose adjustments.",
+                    )
+                with gr.TabItem("eGFR"):
+                    gr.Interface(
+                        fn=calculate_egfr_mcp,
+                        inputs=[
+                            gr.Text(label="Age (years)", value="65"),
+                            gr.Text(label="Serum Creatinine (mg/dL)", value="1.2"),
+                            gr.Radio(["true", "false"], label="Is Female", value="false"),
+                            gr.Radio(["true", "false"], label="Is Black", value="false"),
+                        ],
+                        outputs=gr.JSON(label="eGFR"),
+                        title="CKD-EPI eGFR Calculator",
+                        api_name="ckd_epi",
+                        description="Calculate estimated glomerular filtration rate using CKD-EPI equation.",
+                    )
+                with gr.TabItem("Child-Pugh Score"):
+                    gr.Interface(
+                        fn=calculate_child_pugh_score_mcp,
+                        inputs=[
+                            gr.Text(label="Total Bilirubin (mg/dL)", value="1.5"),
+                            gr.Text(label="Serum Albumin (g/dL)", value="3.5"),
+                            gr.Text(label="INR", value="1.3"),
+                            gr.Dropdown(["none", "mild", "moderate-severe"], value="none", label="Ascites"),
+                            gr.Dropdown(["none", "grade-1-2", "grade-3-4"], value="none", label="Encephalopathy"),
+                        ],
+                        outputs=gr.JSON(label="Child-Pugh Score"),
+                        title="Child-Pugh Score Calculator",
+                        api_name="child_pugh",
+                        description="Calculate Child-Pugh score for liver function assessment and dose adjustments.",
+                    )
+                with gr.TabItem("BMI"):
+                    gr.Interface(
+                        fn=calculate_bmi_mcp,
+                        inputs=[
+                            gr.Text(label="Weight (kg)", value="70"),
+                            gr.Text(label="Height (cm)", value="170"),
+                        ],
+                        outputs=gr.JSON(label="BMI Calculation"),
+                        title="BMI Calculator",
+                        api_name="bmi_calculator",
+                        description="Calculate Body Mass Index and weight category assessment.",
+                    )
+                with gr.TabItem("Ideal Body Weight"):
+                    gr.Interface(
+                        fn=calculate_ideal_body_weight_mcp,
+                        inputs=[
+                            gr.Text(label="Height (cm)", value="170"),
+                            gr.Radio(["true", "false"], label="Is Male", value="true"),
+                        ],
+                        outputs=gr.JSON(label="Ideal Body Weight Calculation"),
+                        title="Ideal Body Weight (IBW) Calculator",
+                        api_name="ideal_body_weight",
+                        description="Calculate Ideal Body Weight using the Devine formula.",
+                    )
+                with gr.TabItem("Dosing Weight"):
+                    gr.Interface(
+                        fn=recommend_dosing_weight_mcp,
+                        inputs=[
+                            gr.Text(label="Actual Weight (kg)", value="85"),
+                            gr.Text(label="Height (cm)", value="170"),
+                            gr.Radio(["true", "false"], label="Is Male", value="true"),
+                        ],
+                        outputs=gr.JSON(label="Dosing Weight Recommendation"),
+                        title="Dosing Weight Calculator",
+                        api_name="dosing_weight",
+                        description="Recommend appropriate weight for medication dosing calculations.",
+                    )
+                with gr.TabItem("Creatinine Converter"):
+                    gr.Interface(
+                        fn=convert_creatinine_units_mcp,
+                        inputs=[
+                            gr.Text(label="Creatinine Value", value="1.2"),
+                            gr.Dropdown(["mg_dl", "umol_l"], value="mg_dl", label="From Unit"),
+                            gr.Dropdown(["mg_dl", "umol_l"], value="umol_l", label="To Unit"),
+                        ],
+                        outputs=gr.JSON(label="Converted Value"),
+                        title="Creatinine Unit Converter",
+                        api_name="creatinine_converter",
+                        description="Convert creatinine values between mg/dL and μmol/L.",
+                    )
+
+        with gr.TabItem("Pharmacovigilance Tools"):
+            with gr.Tabs():
+                with gr.TabItem("Enhanced FAERS Search"):
+                    gr.Interface(
+                        fn=enhanced_faers_search_mcp,
+                        inputs=[
+                            gr.Text(label="Drug Name", placeholder="e.g., lisinopril"),
+                            gr.Text(label="Adverse Event (optional)", placeholder="e.g., cough"),
+                            gr.Text(label="Age Range (optional)", placeholder="e.g., 18-65 or >65"),
+                            gr.Radio(["", "1", "2"], label="Gender (optional)", info="1=Male, 2=Female", value=""),
+                            gr.Radio(["true", "false"], label="Serious Events Only", value="false"),
+                            gr.Number(label="Limit", value=100),
+                        ],
+                        outputs=gr.JSON(label="Output"),
+                        title="Enhanced FAERS Search",
+                        api_name="enhanced_faers_search",
+                        description="Enhanced FAERS search with filtering capabilities for pharmacovigilance analysis.",
+                    )
+                with gr.TabItem("Naranjo Score"):
+                    gr.Interface(
+                        fn=calculate_naranjo_score_mcp,
+                        inputs=[
+                            gr.Radio(["yes", "no", "unknown"], label="Did the adverse reaction appear after the drug was given?", value="unknown", info="Question 2"),
+                            gr.Radio(["yes", "no", "unknown"], label="Did the reaction improve after stopping the drug?", value="unknown", info="Question 3"),
+                            gr.Radio(["yes", "no", "unknown"], label="Did the reaction reappear upon readministration?", value="unknown", info="Question 4"),
+                            gr.Radio(["yes", "no", "unknown"], label="Are there alternative causes for the reaction?", value="unknown", info="Question 5"),
+                            gr.Radio(["yes", "no", "unknown"], label="Did the reaction reappear with a placebo?", value="unknown", info="Question 6"),
+                            gr.Radio(["yes", "no", "unknown"], label="Was the drug detected in blood/fluids at a toxic level?", value="unknown", info="Question 7"),
+                            gr.Radio(["yes", "no", "unknown"], label="Did the reaction change with dose alterations?", value="unknown", info="Question 8"),
+                            gr.Radio(["yes", "no", "unknown"], label="Did the patient have a similar reaction previously?", value="unknown", info="Question 9"),
+                            gr.Radio(["yes", "no", "unknown"], label="Was the adverse event confirmed objectively?", value="unknown", info="Question 10"),
+                            # This argument seems to be a duplicate or a more specific version of the first one. Let's provide a clear label.
+                            gr.Radio(["yes", "no", "unknown"], label="Are there conclusive reports on this reaction?", value="unknown", info="Question 1"),
+                        ],
+                        outputs=gr.JSON(label="Naranjo Score"),
+                        title="Naranjo Score Calculator",
+                        api_name="naranjo_score",
+                        description="Calculate the Naranjo Adverse Drug Reaction Probability Scale.",
+                    )
+                with gr.TabItem("Disproportionality Analysis"):
+                    gr.Interface(
+                        fn=disproportionality_analysis_mcp,
+                        inputs=[
+                            gr.Text(label="Drug Name", placeholder="e.g., atorvastatin"),
+                            gr.Text(label="Adverse Event", placeholder="e.g., myalgia"),
+                            gr.Number(label="Background Limit", value=10000),
+                        ],
+                        outputs=gr.JSON(label="Output"),
+                        title="Disproportionality Analysis (Signal Detection)",
+                        api_name="disproportionality_analysis",
+                        description="Perform disproportionality analysis (PRR, ROR, IC) to detect potential drug-adverse event signals.",
+                    )
+                with gr.TabItem("Similar Case Finder"):
+                    gr.Interface(
+                        fn=find_similar_cases_mcp,
+                        inputs=[
+                            gr.Text(label="Reference FAERS Case ID"),
+                            gr.Slider(0, 1, value=0.7, label="Similarity Threshold"),
+                            gr.Number(label="Limit", value=50),
+                        ],
+                        outputs=gr.JSON(label="Output"),
+                        title="Find Similar Cases",
+                        api_name="find_similar_cases",
+                        description="Find cases similar to a reference case based on patient characteristics, drugs, and adverse events.",
+                    )
+                with gr.TabItem("Temporal Analysis"):
+                    gr.Interface(
+                        fn=temporal_analysis_mcp,
+                        inputs=[
+                            gr.Text(label="Drug Name"),
+                            gr.Text(label="Adverse Event (optional)"),
+                            gr.Number(label="Limit", value=500),
+                        ],
+                        outputs=gr.JSON(label="Output"),
+                        title="Temporal Analysis",
+                        api_name="temporal_analysis",
+                        description="Analyze temporal patterns and time-to-onset of adverse events for a drug.",
+                    )
 
 if __name__ == "__main__":
     demo.launch(mcp_server=True, show_error=True)

requirements.txt

@@ -4,4 +4,6 @@ gradio
 datasets
 apscheduler
 beautifulsoup4
-lxml
+lxml
+mlx-lm
+huggingface_hub[mcp]>=0.32.0