Merge pull request #24 from insightbuilder/mcp-excel-server

got the report generation working after the coding logic was corrected

Author: insightbuilder

mcp_excel_server/mcpclient.py

@@ -123,22 +123,24 @@ async def process_query(self, query: str) -> str:
                 )
 
                 final_text.append(response.content[0].text)
-
         return "\n".join(final_text)
 
     async def chat_loop(self):
         """Run an interactive chat loop"""
         print("\nMCP Client Started!")
         print("Type your queries or 'quit' to exit.")
-
+        reply_history = ""
         while True:
             try:
                 query = input("\nInteract with Excel File here: ").strip()
-
+                query_with_history = (
+                    f"Previous conversation:\n{reply_history}\n Query: {query}"
+                )
                 if query.lower() == "quit":
                     break
 
-                response = await self.process_query(query)
+                response = await self.process_query(query_with_history)
+                reply_history += f"Query: {query}\nResponse: {response}\n"
                 print("\n" + response)
 
             except Exception as e:

mcp_excel_server/report_1951.md

@@ -0,0 +1,57 @@
+# Exercise Data Analysis Report
+
+## Summary Statistics
+
+### Numerical Variables
+
+#### Calories Burn
+- Mean: 309.68
+- Minimum: 103.34
+- Maximum: 497.55
+- Standard Deviation: 111.65
+
+#### Dream Weight
+- Mean: 77.02
+- Minimum: 52.73
+- Maximum: 95.20
+- Standard Deviation: 12.39
+
+#### Actual Weight
+- Mean: 77.32
+- Minimum: 54.14
+- Maximum: 97.44
+- Standard Deviation: 13.76
+
+#### Age
+- Mean: 38.65
+- Minimum: 18
+- Maximum: 60
+- Standard Deviation: 13.81
+
+#### Heart Rate
+- Mean: 137.40
+- Minimum: 103
+- Maximum: 174
+- Standard Deviation: 24.19
+
+#### BMI
+- Mean: 28.80
+- Minimum: 20.45
+- Maximum: 34.72
+- Standard Deviation: 5.02
+
+## Categorical Variables Distribution
+
+### Gender
+- Male: 14 (70%)
+- Female: 6 (30%)
+
+### Weather Conditions
+- Cloudy: 7 (35%)
+- Rainy: 6 (30%)
+- Sunny: 7 (35%)
+
+### Exercise Intensity
+- 1-3 intensity level: 5 participants
+- 4-6 intensity level: 6 participants
+- 7-10 intensity level: 9 participants

mcp_excel_server/server.py

@@ -3,14 +3,10 @@
 import os
 from pathlib import Path
 from html import escape
-from anthropic import Anthropic
 
 
-anthropic = Anthropic()
 mcp = FastMCP("mcp-excel-server")
 
-global analysis_data
-
 
 @mcp.tool()
 def xlsx_to_html_table(
@@ -98,41 +94,6 @@ def get_col_name(file_path: str = "test.xlsx", sheet_name: str = "Sheet1") -> st
         return f"There was issue in reading the data: {e}"
 
 
-def analyse_table(
-    file_path: str = "test.xlsx", sheet_name: str = "Sheet1", has_headers: bool = True
-) -> str:
-    """Use this tool when the user specifically asks for an analysis of the given file.
-    The entire excel sheet is read into a html table format, and then analysed by an expert analyst.
-    Expect a feedback from the analyst on the report completion."""
-
-    try:
-        final_html = xlsx_to_html_table(file_path, sheet_name, has_headers)
-        # sending the html to AI model for analysis
-
-        hal_analysis_system = """You are hal4025, an expert in working on excel sheets.
-                    You are very good in analysing xlsx files and providing the report.
-                    Do not apologize. Do not provide guidance or examples. 
-                    Do not share what you cannot do.
-                    Please do not provide the python code for the user requests.
-                    Users don't know to code.
-                    Do not explain how analyis is being done."""
-
-        messages = [{"role": "user", "content": final_html}]
-        print(final_html)
-        response = anthropic.messages.create(
-            model="claude-3-5-haiku-20241022",
-            max_tokens=1000,
-            system=hal_analysis_system,
-            messages=messages,
-        )
-        analysis_result = f"The analysis result {response.content[0].text}"
-
-        return f"The analysis is ready. {analysis_result}."
-
-    except Exception as e:
-        return f"Unable to complete the analysis due to : {e}"
-
-
 @mcp.tool()
 def read_excel_file_cell(
     file_path: str = "test.xlsx",
@@ -220,7 +181,7 @@ def search_excel_sheet_for_value(
     value_to_find: str = "5",
     match_case: bool = True,
 ):
-    """Use this tool when a value_to_find has to to be located
+    """Use this tool when  user asks to find to value_to_find data
     inside a excel file at the file_path"""
     wb = load_workbook(file_path)
     ws = wb[sheet_name]
@@ -243,15 +204,14 @@ def search_excel_sheet_for_value(
 
 
 @mcp.tool()
-def write_analysis_md(
-    file_path: str = "analysis_report.md",
+def write_report(
+    text_data: str,
+    file_path: str,
 ):
-    """Use this tool whenthe analysis report has to be written to the file.
-    The data is taken from the analysis_data global variable, no need to look for data from outside.
+    """Use this tool when the user wants some data to be written to the file.
     New report file will be generated every time, and you will get confirmation"""
     import uuid
 
-    global analysis_data
     try:
         uid = uuid.uuid4()
         ver = str(uid)[:4]
@@ -262,15 +222,10 @@ def write_analysis_md(
             file_ver = f"{filename}_{ver}.md"
         else:
             file_ver = f"{file_path}_{ver}.md"
-        if analysis_data != "":
-            with open(file_ver, "w") as anw:
-                anw.write(analysis_data)
 
-            # after writing analysis data, reset the global variable
-            analysis_data = ""
-            return f"The report has been written to {file_ver}"
-        else:
-            return "The analysis data is empty. Kindly get the analysis done."
+        with open(file_ver, "w") as anw:
+            anw.write(text_data)
+        return f"The report has been written to {file_ver}"
     except Exception as e:
         return f"There was issue in writing report: {e}"