chore(pre-commit): apply autofixes

.pre-commit-config.yaml

@@ -0,0 +1,14 @@
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.6.0
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-yaml
+      - id: check-merge-conflict
+
+  - repo: https://github.com/Yelp/detect-secrets
+    rev: v1.5.0
+    hooks:
+      - id: detect-secrets
+        args: ["--baseline", ".secrets.baseline"]

.secrets.baseline

@@ -0,0 +1,127 @@
+{
+  "version": "1.5.0",
+  "plugins_used": [
+    {
+      "name": "ArtifactoryDetector"
+    },
+    {
+      "name": "AWSKeyDetector"
+    },
+    {
+      "name": "AzureStorageKeyDetector"
+    },
+    {
+      "name": "Base64HighEntropyString",
+      "limit": 4.5
+    },
+    {
+      "name": "BasicAuthDetector"
+    },
+    {
+      "name": "CloudantDetector"
+    },
+    {
+      "name": "DiscordBotTokenDetector"
+    },
+    {
+      "name": "GitHubTokenDetector"
+    },
+    {
+      "name": "GitLabTokenDetector"
+    },
+    {
+      "name": "HexHighEntropyString",
+      "limit": 3.0
+    },
+    {
+      "name": "IbmCloudIamDetector"
+    },
+    {
+      "name": "IbmCosHmacDetector"
+    },
+    {
+      "name": "IPPublicDetector"
+    },
+    {
+      "name": "JwtTokenDetector"
+    },
+    {
+      "name": "KeywordDetector",
+      "keyword_exclude": ""
+    },
+    {
+      "name": "MailchimpDetector"
+    },
+    {
+      "name": "NpmDetector"
+    },
+    {
+      "name": "OpenAIDetector"
+    },
+    {
+      "name": "PrivateKeyDetector"
+    },
+    {
+      "name": "PypiTokenDetector"
+    },
+    {
+      "name": "SendGridDetector"
+    },
+    {
+      "name": "SlackDetector"
+    },
+    {
+      "name": "SoftlayerDetector"
+    },
+    {
+      "name": "SquareOAuthDetector"
+    },
+    {
+      "name": "StripeDetector"
+    },
+    {
+      "name": "TelegramBotTokenDetector"
+    },
+    {
+      "name": "TwilioKeyDetector"
+    }
+  ],
+  "filters_used": [
+    {
+      "path": "detect_secrets.filters.allowlist.is_line_allowlisted"
+    },
+    {
+      "path": "detect_secrets.filters.common.is_ignored_due_to_verification_policies",
+      "min_level": 2
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_indirect_reference"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_likely_id_string"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_lock_file"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_not_alphanumeric_string"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_potential_uuid"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_prefixed_with_dollar_sign"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_sequential_string"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_swagger_file"
+    },
+    {
+      "path": "detect_secrets.filters.heuristic.is_templated_secret"
+    }
+  ],
+  "results": {},
+  "generated_at": "2025-09-27T13:56:05Z"
+}

.vscode/launch.json

@@ -12,4 +12,4 @@
             "console": "integratedTerminal"
         }
     ]
-}
+}

mcp_architecture_diagram.txt

@@ -52,4 +52,4 @@
      |   - No network overhead       - Authentication       |
      +------------------------------------------------------+
 
-```
+```

mcp_chatbot.py

@@ -21,7 +21,7 @@ class MCP_ChatBot:
     async def process_query(self, query):
         messages = [{'role':'user', 'content':query}]
         response = self.anthropic.messages.create(max_tokens = 2024,
-                                      model = 'claude-3-7-sonnet-20250219', 
+                                      model = 'claude-3-7-sonnet-20250219',
                                       tools = self.available_tools, # tools exposed to the LLM
                                       messages = messages)
         process_query = True
@@ -46,7 +46,7 @@ class MCP_ChatBot:
                     #result = execute_tool(tool_name, tool_args): not anymore needed
                     # tool invocation through the client session
                     result = await self.session.call_tool(tool_name, arguments=tool_args)
-                    messages.append({"role": "user", 
+                    messages.append({"role": "user",
                                       "content": [
                                           {
                                               "type": "tool_result",
@@ -56,9 +56,9 @@ class MCP_ChatBot:
                                       ]
                                     })
                     response = self.anthropic.messages.create(max_tokens = 2024,
-                                      model = 'claude-3-7-sonnet-20250219', 
+                                      model = 'claude-3-7-sonnet-20250219',
                                       tools = self.available_tools,
-                                      messages = messages) 
+                                      messages = messages)
 
                     if(len(response.content) == 1 and response.content[0].type == "text"):
                         print(response.content[0].text)

mcp_chatbot_L7.py

@@ -19,7 +19,7 @@ class MCP_ChatBot:
         self.anthropic = Anthropic()
         # Tools list required for Anthropic API
         self.available_tools = []
-        # Prompts list for quick display 
+        # Prompts list for quick display
         self.available_prompts = []
         # Sessions dict maps tool/prompt names or resource URIs to MCP client sessions
         self.sessions = {}
@@ -35,8 +35,8 @@ class MCP_ChatBot:
                 ClientSession(read, write)
             )
             await session.initialize()
-            
-            
+
+
             try:
                 # List available tools
                 response = await session.list_tools()
@@ -47,7 +47,7 @@ class MCP_ChatBot:
                         "description": tool.description,
                         "input_schema": tool.inputSchema
                     })
-            
+
                 # List available prompts
                 prompts_response = await session.list_prompts()
                 if prompts_response and prompts_response.prompts:
@@ -64,10 +64,10 @@ class MCP_ChatBot:
                     for resource in resources_response.resources:
                         resource_uri = str(resource.uri)
                         self.sessions[resource_uri] = session
-            
+
             except Exception as e:
                 print(f"Error {e}")
-                
+
         except Exception as e:
             print(f"Error connecting to {server_name}: {e}")
 
@@ -76,28 +76,28 @@ class MCP_ChatBot:
             with open("server_config_L7.json", "r") as file:
                 data = json.load(file)
             servers = data.get("mcpServers", {})
-            print(f"Debug - servers: {servers}") 
+            print(f"Debug - servers: {servers}")
 
             for server_name, server_config in servers.items():
                 await self.connect_to_server(server_name, server_config)
         except Exception as e:
             print(f"Error loading server config: {e}")
             raise
-    
+
     async def process_query(self, query):
         messages = [{'role':'user', 'content':query}]
-        
+
         while True:
             response = self.anthropic.messages.create(
                 max_tokens = 2024,
-                model = 'claude-3-7-sonnet-20250219', 
+                model = 'claude-3-7-sonnet-20250219',
                 tools = self.available_tools,
                 messages = messages
             )
-            
+
             assistant_content = []
             has_tool_use = False
-            
+
             for content in response.content:
                 if content.type == 'text':
                     print(content.text)
@@ -106,16 +106,16 @@ class MCP_ChatBot:
                     has_tool_use = True
                     assistant_content.append(content)
                     messages.append({'role':'assistant', 'content':assistant_content})
-                    
+
                     # Get session and call tool
                     session = self.sessions.get(content.name)
                     if not session:
                         print(f"Tool '{content.name}' not found.")
                         break
-                        
+
                     result = await session.call_tool(content.name, arguments=content.input)
                     messages.append({
-                        "role": "user", 
+                        "role": "user",
                         "content": [
                             {
                                 "type": "tool_result",
@@ -124,25 +124,25 @@ class MCP_ChatBot:
                             }
                         ]
                     })
-            
+
             # Exit loop if no tool was used
             if not has_tool_use:
                 break
 
     async def get_resource(self, resource_uri):
         session = self.sessions.get(resource_uri)
-        
+
         # Fallback for papers URIs - try any papers resource session
         if not session and resource_uri.startswith("papers://"):
             for uri, sess in self.sessions.items():
                 if uri.startswith("papers://"):
                     session = sess
                     break
-            
+
         if not session:
             print(f"Resource '{resource_uri}' not found.")
             return
-        
+
         try:
             result = await session.read_resource(uri=resource_uri)
             if result and result.contents:
@@ -153,13 +153,13 @@ class MCP_ChatBot:
                 print("No content available.")
         except Exception as e:
             print(f"Error: {e}")
-    
+
     async def list_prompts(self):
         """List all available prompts."""
         if not self.available_prompts:
             print("No prompts available.")
             return
-        
+
         print("\nAvailable prompts:")
         for prompt in self.available_prompts:
             print(f"- {prompt['name']}: {prompt['description']}")
@@ -168,19 +168,19 @@ class MCP_ChatBot:
                 for arg in prompt['arguments']:
                     arg_name = arg.name if hasattr(arg, 'name') else arg.get('name', '')
                     print(f"    - {arg_name}")
-    
+
     async def execute_prompt(self, prompt_name, args):
         """Execute a prompt with the given arguments."""
         session = self.sessions.get(prompt_name)
         if not session:
             print(f"Prompt '{prompt_name}' not found.")
             return
-        
+
         try:
             result = await session.get_prompt(prompt_name, arguments=args)
             if result and result.messages:
                 prompt_content = result.messages[0].content
-                
+
                 # Extract text from content (handles different formats)
                 if isinstance(prompt_content, str):
                     text = prompt_content
@@ -188,14 +188,14 @@ class MCP_ChatBot:
                     text = prompt_content.text
                 else:
                     # Handle list of content items
-                    text = " ".join(item.text if hasattr(item, 'text') else str(item) 
+                    text = " ".join(item.text if hasattr(item, 'text') else str(item)
                                   for item in prompt_content)
-                
+
                 print(f"\nExecuting prompt '{prompt_name}'...")
                 await self.process_query(text)
         except Exception as e:
             print(f"Error: {e}")
-    
+
     async def chat_loop(self):
         print("\nMCP Chatbot Started 7!")
         print("Type your queries or 'quit' to exit.")
@@ -203,19 +203,19 @@ class MCP_ChatBot:
         print("Use @<topic> to search papers in that topic")
         print("Use /prompts to list available prompts")
         print("Use /prompt <name> <arg1=value1> to execute a prompt")
-        
+
         while True:
             try:
                 query = input("\nQuery: ").strip()
                 if not query:
                     continue
-        
+
                 if query.lower() == 'quit':
                     break
-                
+
                 # Check for @resource syntax first
                 if query.startswith('@'):
-                    # Remove @ sign  
+                    # Remove @ sign
                     topic = query[1:]
                     if topic == "folders":
                         resource_uri = "papers://folders"
@@ -223,38 +223,38 @@ class MCP_ChatBot:
                         resource_uri = f"papers://{topic}"
                     await self.get_resource(resource_uri)
                     continue
-                
+
                 # Check for /command syntax
                 if query.startswith('/'):
                     parts = query.split()
                     command = parts[0].lower()
-                    
+
                     if command == '/prompts':
                         await self.list_prompts()
                     elif command == '/prompt':
                         if len(parts) < 2:
                             print("Usage: /prompt <name> <arg1=value1> <arg2=value2>")
                             continue
-                        
+
                         prompt_name = parts[1]
                         args = {}
-                        
+
                         # Parse arguments
                         for arg in parts[2:]:
                             if '=' in arg:
                                 key, value = arg.split('=', 1)
                                 args[key] = value
-                        
+
                         await self.execute_prompt(prompt_name, args)
                     else:
                         print(f"Unknown command: {command}")
                     continue
-                
+
                 await self.process_query(query)
-                    
+
             except Exception as e:
                 print(f"\nError: {str(e)}")
-    
+
     async def cleanup(self):
         await self.exit_stack.aclose()
 
@@ -269,4 +269,4 @@ async def main():
 
 
 if __name__ == "__main__":
-    asyncio.run(main())
+    asyncio.run(main())

mcp_chatbot_v2.py

@@ -74,7 +74,7 @@ class MCP_ChatBot:
     async def process_query(self, query):
         messages = [{'role':'user', 'content':query}]
         response = self.anthropic.messages.create(max_tokens = 2024,
-                                      model = 'claude-3-7-sonnet-20250219', 
+                                      model = 'claude-3-7-sonnet-20250219',
                                       tools = self.available_tools,
                                       messages = messages)
         process_query = True
@@ -99,7 +99,7 @@ class MCP_ChatBot:
                     # Call a tool
                     session = self.tool_to_session[tool_name] # new
                     result = await session.call_tool(tool_name, arguments=tool_args)
-                    messages.append({"role": "user", 
+                    messages.append({"role": "user",
                                       "content": [
                                           {
                                               "type": "tool_result",
@@ -109,9 +109,9 @@ class MCP_ChatBot:
                                       ]
                                     })
                     response = self.anthropic.messages.create(max_tokens = 2024,
-                                      model = 'claude-3-7-sonnet-20250219', 
+                                      model = 'claude-3-7-sonnet-20250219',
                                       tools = self.available_tools,
-                                      messages = messages) 
+                                      messages = messages)
 
                     if(len(response.content) == 1 and response.content[0].type == "text"):
                         print(response.content[0].text)
@@ -148,10 +148,10 @@ async def main():
         # the mcp clients and sessions are not initialized using "with"
         # like in the previous lesson
         # so the cleanup should be manually handled
-        await chatbot.connect_to_servers() # new! 
+        await chatbot.connect_to_servers() # new!
         await chatbot.chat_loop()
     finally:
-        await chatbot.cleanup() #new! 
+        await chatbot.cleanup() #new!
 
 
 if __name__ == "__main__":

mcp_chatbot_v3.py

@@ -17,7 +17,7 @@ class MCP_ChatBot:
         self.anthropic = Anthropic()
         # Tools list required for Anthropic API
         self.available_tools = []
-        # Prompts list for quick display 
+        # Prompts list for quick display
         self.available_prompts = []
         # Sessions dict maps tool/prompt names or resource URIs to MCP client sessions
         self.sessions = {}
@@ -33,8 +33,8 @@ class MCP_ChatBot:
                 ClientSession(read, write)
             )
             await session.initialize()
-            
-            
+
+
             try:
                 # List available tools
                 response = await session.list_tools()
@@ -45,7 +45,7 @@ class MCP_ChatBot:
                         "description": tool.description,
                         "input_schema": tool.inputSchema
                     })
-            
+
                 # List available prompts
                 prompts_response = await session.list_prompts()
                 if prompts_response and prompts_response.prompts:
@@ -62,10 +62,10 @@ class MCP_ChatBot:
                     for resource in resources_response.resources:
                         resource_uri = str(resource.uri)
                         self.sessions[resource_uri] = session
-            
+
             except Exception as e:
                 print(f"Error {e}")
-                
+
         except Exception as e:
             print(f"Error connecting to {server_name}: {e}")
 
@@ -79,21 +79,21 @@ class MCP_ChatBot:
         except Exception as e:
             print(f"Error loading server config: {e}")
             raise
-    
+
     async def process_query(self, query):
         messages = [{'role':'user', 'content':query}]
-        
+
         while True:
             response = self.anthropic.messages.create(
                 max_tokens = 2024,
-                model = 'claude-3-7-sonnet-20250219', 
+                model = 'claude-3-7-sonnet-20250219',
                 tools = self.available_tools,
                 messages = messages
             )
-            
+
             assistant_content = []
             has_tool_use = False
-            
+
             for content in response.content:
                 if content.type == 'text':
                     print(content.text)
@@ -102,16 +102,16 @@ class MCP_ChatBot:
                     has_tool_use = True
                     assistant_content.append(content)
                     messages.append({'role':'assistant', 'content':assistant_content})
-                    
+
                     # Get session and call tool
                     session = self.sessions.get(content.name)
                     if not session:
                         print(f"Tool '{content.name}' not found.")
                         break
-                        
+
                     result = await session.call_tool(content.name, arguments=content.input)
                     messages.append({
-                        "role": "user", 
+                        "role": "user",
                         "content": [
                             {
                                 "type": "tool_result",
@@ -120,25 +120,25 @@ class MCP_ChatBot:
                             }
                         ]
                     })
-            
+
             # Exit loop if no tool was used
             if not has_tool_use:
                 break
 
     async def get_resource(self, resource_uri):
         session = self.sessions.get(resource_uri)
-        
+
         # Fallback for papers URIs - try any papers resource session
         if not session and resource_uri.startswith("papers://"):
             for uri, sess in self.sessions.items():
                 if uri.startswith("papers://"):
                     session = sess
                     break
-            
+
         if not session:
             print(f"Resource '{resource_uri}' not found.")
             return
-        
+
         try:
             result = await session.read_resource(uri=resource_uri)
             if result and result.contents:
@@ -149,13 +149,13 @@ class MCP_ChatBot:
                 print("No content available.")
         except Exception as e:
             print(f"Error: {e}")
-    
+
     async def list_prompts(self):
         """List all available prompts."""
         if not self.available_prompts:
             print("No prompts available.")
             return
-        
+
         print("\nAvailable prompts:")
         for prompt in self.available_prompts:
             print(f"- {prompt['name']}: {prompt['description']}")
@@ -164,19 +164,19 @@ class MCP_ChatBot:
                 for arg in prompt['arguments']:
                     arg_name = arg.name if hasattr(arg, 'name') else arg.get('name', '')
                     print(f"    - {arg_name}")
-    
+
     async def execute_prompt(self, prompt_name, args):
         """Execute a prompt with the given arguments."""
         session = self.sessions.get(prompt_name)
         if not session:
             print(f"Prompt '{prompt_name}' not found.")
             return
-        
+
         try:
             result = await session.get_prompt(prompt_name, arguments=args)
             if result and result.messages:
                 prompt_content = result.messages[0].content
-                
+
                 # Extract text from content (handles different formats)
                 if isinstance(prompt_content, str):
                     text = prompt_content
@@ -184,14 +184,14 @@ class MCP_ChatBot:
                     text = prompt_content.text
                 else:
                     # Handle list of content items
-                    text = " ".join(item.text if hasattr(item, 'text') else str(item) 
+                    text = " ".join(item.text if hasattr(item, 'text') else str(item)
                                   for item in prompt_content)
-                
+
                 print(f"\nExecuting prompt '{prompt_name}'...")
                 await self.process_query(text)
         except Exception as e:
             print(f"Error: {e}")
-    
+
     async def chat_loop(self):
         print("\nMCP Chatbot Started!")
         print("Type your queries or 'quit' to exit.")
@@ -199,19 +199,19 @@ class MCP_ChatBot:
         print("Use @<topic> to search papers in that topic")
         print("Use /prompts to list available prompts")
         print("Use /prompt <name> <arg1=value1> to execute a prompt")
-        
+
         while True:
             try:
                 query = input("\nQuery: ").strip()
                 if not query:
                     continue
-        
+
                 if query.lower() == 'quit':
                     break
-                
+
                 # Check for @resource syntax first
                 if query.startswith('@'):
-                    # Remove @ sign  
+                    # Remove @ sign
                     topic = query[1:]
                     if topic == "folders":
                         resource_uri = "papers://folders"
@@ -219,38 +219,38 @@ class MCP_ChatBot:
                         resource_uri = f"papers://{topic}"
                     await self.get_resource(resource_uri)
                     continue
-                
+
                 # Check for /command syntax
                 if query.startswith('/'):
                     parts = query.split()
                     command = parts[0].lower()
-                    
+
                     if command == '/prompts':
                         await self.list_prompts()
                     elif command == '/prompt':
                         if len(parts) < 2:
                             print("Usage: /prompt <name> <arg1=value1> <arg2=value2>")
                             continue
-                        
+
                         prompt_name = parts[1]
                         args = {}
-                        
+
                         # Parse arguments
                         for arg in parts[2:]:
                             if '=' in arg:
                                 key, value = arg.split('=', 1)
                                 args[key] = value
-                        
+
                         await self.execute_prompt(prompt_name, args)
                     else:
                         print(f"Unknown command: {command}")
                     continue
-                
+
                 await self.process_query(query)
-                    
+
             except Exception as e:
                 print(f"\nError: {str(e)}")
-    
+
     async def cleanup(self):
         await self.exit_stack.aclose()
 
@@ -265,4 +265,4 @@ async def main():
 
 
 if __name__ == "__main__":
-    asyncio.run(main())
+    asyncio.run(main())

mcp_diagram.txt

@@ -58,4 +58,4 @@
 | - Resources        |                   | - Elicitation        |
 | - Prompts          |                   | - Logging            |
 +--------------------+                   +----------------------+
-```
+```

mcp_summary.md

@@ -63,4 +63,4 @@ Each primitive type has associated methods for discovery (`*/list`), retrieval (
 
 #### Notifications
 
-The protocol supports real-time notifications to enable dynamic updates between servers and clients, sent as JSON-RPC 2.0 notification messages without expecting a response.
+The protocol supports real-time notifications to enable dynamic updates between servers and clients, sent as JSON-RPC 2.0 notification messages without expecting a response.

papers/algebra/papers_info.json

@@ -45,4 +45,4 @@
     "pdf_url": "http://arxiv.org/pdf/math/0506093v1",
     "published": "2005-06-06"
   }
-}
+}

papers/artificial_intelligence/papers_info.json

@@ -47,4 +47,4 @@
     "pdf_url": "http://arxiv.org/pdf/1304.3846v1",
     "published": "2013-04-13"
   }
-}
+}

papers/chemistry/papers_info.json

@@ -68,4 +68,4 @@
     "pdf_url": "http://arxiv.org/pdf/2109.12552v1",
     "published": "2021-09-26"
   }
-}
+}

papers/computers/papers_info.json

@@ -47,4 +47,4 @@
     "pdf_url": "http://arxiv.org/pdf/2403.03925v1",
     "published": "2024-03-06"
   }
-}
+}

papers/deepseek/papers_info.json

@@ -24,4 +24,4 @@
     "pdf_url": "http://arxiv.org/pdf/2503.00624v1",
     "published": "2025-03-01"
   }
-}
+}

papers/gpt-5/papers_info.json

@@ -22,4 +22,4 @@
     "pdf_url": "http://arxiv.org/pdf/2508.19259v1",
     "published": "2025-08-16"
   }
-}
+}

papers/intelligence/papers_info.json

@@ -52,4 +52,4 @@
     "pdf_url": "http://arxiv.org/pdf/2409.14496v1",
     "published": "2024-09-22"
   }
-}
+}

papers/large_language_model/papers_info.json

@@ -50,4 +50,4 @@
     "pdf_url": "http://arxiv.org/pdf/2404.09579v1",
     "published": "2024-04-15"
   }
-}
+}

papers/large_language_models/papers_info.json

@@ -50,4 +50,4 @@
     "pdf_url": "http://arxiv.org/pdf/2404.09579v1",
     "published": "2024-04-15"
   }
-}
+}

papers/llm_evaluation/papers_info.json

@@ -30,4 +30,4 @@
     "pdf_url": "http://arxiv.org/pdf/2410.07069v1",
     "published": "2024-10-09"
   }
-}
+}

papers/physics/papers_info.json

@@ -50,4 +50,4 @@
     "pdf_url": "http://arxiv.org/pdf/1405.5530v1",
     "published": "2014-05-22"
   }
-}
+}

papers/transformer_attention_nlp/papers_info.json

@@ -36,4 +36,4 @@
     "pdf_url": "http://arxiv.org/pdf/2202.07856v2",
     "published": "2022-02-16"
   }
-}
+}

papers/transformer_neural_networks/papers_info.json

@@ -33,4 +33,4 @@
     "pdf_url": "http://arxiv.org/pdf/2112.12345v1",
     "published": "2021-12-23"
   }
-}
+}

papers/transformers/papers_info.json

@@ -27,4 +27,4 @@
     "pdf_url": "http://arxiv.org/pdf/1605.08683v1",
     "published": "2016-05-27"
   }
-}
+}

research_server.py

@@ -15,16 +15,16 @@ mcp = FastMCP("research")
 def search_papers(topic: str, max_results: int = 5) -> List[str]:
     """
     Search for papers on arXiv based on a topic and store their information.
-    
+
     Args:
         topic: The topic to search for
         max_results: Maximum number of results to retrieve (default: 5)
-        
+
     Returns:
         List of paper IDs found in the search
     """
-    
-    # Use arxiv to find the papers 
+
+    # Use arxiv to find the papers
     client = arxiv.Client()
 
     # Search for the most relevant articles matching the queried topic
@@ -35,11 +35,11 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
     )
 
     papers = client.results(search)
-    
+
     # Create directory for this topic
     path = os.path.join(PAPER_DIR, topic.lower().replace(" ", "_"))
     os.makedirs(path, exist_ok=True)
-    
+
     file_path = os.path.join(path, "papers_info.json")
 
     # Try to load existing papers info
@@ -49,7 +49,7 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
     except (FileNotFoundError, json.JSONDecodeError):
         papers_info = {}
 
-    # Process each paper and add to papers_info  
+    # Process each paper and add to papers_info
     paper_ids = []
     for paper in papers:
         paper_ids.append(paper.get_short_id())
@@ -61,27 +61,27 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
             'published': str(paper.published.date())
         }
         papers_info[paper.get_short_id()] = paper_info
-    
+
     # Save updated papers_info to json file
     with open(file_path, "w") as json_file:
         json.dump(papers_info, json_file, indent=2)
-    
+
     print(f"Results are saved in: {file_path}")
-    
+
     return paper_ids
 
 @mcp.tool()
 def extract_info(paper_id: str) -> str:
     """
     Search for information about a specific paper across all topic directories.
-    
+
     Args:
         paper_id: The ID of the paper to look for
-        
+
     Returns:
         JSON string with paper information if found, error message if not found
     """
- 
+
     for item in os.listdir(PAPER_DIR):
         item_path = os.path.join(PAPER_DIR, item)
         if os.path.isdir(item_path):
@@ -95,7 +95,7 @@ def extract_info(paper_id: str) -> str:
                 except (FileNotFoundError, json.JSONDecodeError) as e:
                     print(f"Error reading {file_path}: {str(e)}")
                     continue
-    
+
     return f"There's no saved information related to paper {paper_id}."
 
 

research_server_L7.py

@@ -38,16 +38,16 @@ mcp = FastMCP("research")
 def search_papers(topic: str, max_results: int = 5) -> List[str]:
     """
     Search for papers on arXiv based on a topic and store their information.
-    
+
     Args:
         topic: The topic to search for
         max_results: Maximum number of results to retrieve (default: 5)
-        
+
     Returns:
         List of paper IDs found in the search
     """
-    
-    # Use arxiv to find the papers 
+
+    # Use arxiv to find the papers
     client = arxiv.Client()
 
     # Search for the most relevant articles matching the queried topic
@@ -58,11 +58,11 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
     )
 
     papers = client.results(search)
-    
+
     # Create directory for this topic
     path = os.path.join(PAPER_DIR, topic.lower().replace(" ", "_"))
     os.makedirs(path, exist_ok=True)
-    
+
     file_path = os.path.join(path, "papers_info.json")
 
     # Try to load existing papers info
@@ -72,7 +72,7 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
     except (FileNotFoundError, json.JSONDecodeError):
         papers_info = {}
 
-    # Process each paper and add to papers_info  
+    # Process each paper and add to papers_info
     paper_ids = []
     for paper in papers:
         paper_ids.append(paper.get_short_id())
@@ -84,27 +84,27 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
             'published': str(paper.published.date())
         }
         papers_info[paper.get_short_id()] = paper_info
-    
+
     # Save updated papers_info to json file
     with open(file_path, "w") as json_file:
         json.dump(papers_info, json_file, indent=2)
-    
+
     print(f"Results are saved in: {file_path}")
-    
+
     return paper_ids
 
 @mcp.tool()
 def extract_info(paper_id: str) -> str:
     """
     Search for information about a specific paper across all topic directories.
-    
+
     Args:
         paper_id: The ID of the paper to look for
-        
+
     Returns:
         JSON string with paper information if found, error message if not found
     """
- 
+
     for item in os.listdir(PAPER_DIR):
         item_path = os.path.join(PAPER_DIR, item)
         if os.path.isdir(item_path):
@@ -118,7 +118,7 @@ def extract_info(paper_id: str) -> str:
                 except (FileNotFoundError, json.JSONDecodeError) as e:
                     print(f"Error reading {file_path}: {str(e)}")
                     continue
-    
+
     return f"There's no saved information related to paper {paper_id}."
 
 
@@ -127,11 +127,11 @@ def extract_info(paper_id: str) -> str:
 def get_available_folders() -> str:
     """
     List all available topic folders in the papers directory.
-    
+
     This resource provides a simple list of all available topic folders.
     """
     folders = []
-    
+
     # Get all topic directories
     if os.path.exists(PAPER_DIR):
         for topic_dir in os.listdir(PAPER_DIR):
@@ -141,7 +141,7 @@ def get_available_folders() -> str:
                 papers_file = os.path.join(topic_path, "papers_info.json")
                 if os.path.exists(papers_file):
                     folders.append(topic_dir)
-    
+
     # Create a simple markdown list
     content = "# Available Topics\n\n"
     if folders:
@@ -150,31 +150,31 @@ def get_available_folders() -> str:
         content += f"\nUse @{folder} to access papers in that topic.\n"
     else:
         content += "No topics found.\n"
-    
+
     return content
 
 @mcp.resource("papers://{topic}")
 def get_topic_papers(topic: str) -> str:
     """
     Get detailed information about papers on a specific topic.
-    
+
     Args:
         topic: The research topic to retrieve papers for
     """
     topic_dir = topic.lower().replace(" ", "_")
     papers_file = os.path.join(PAPER_DIR, topic_dir, "papers_info.json")
-    
+
     if not os.path.exists(papers_file):
         return f"# No papers found for topic: {topic}\n\nTry searching for papers on this topic first."
-    
+
     try:
         with open(papers_file, 'r') as f:
             papers_data = json.load(f)
-        
+
         # Create markdown content with paper details
         content = f"# Papers on {topic.replace('_', ' ').title()}\n\n"
         content += f"Total papers: {len(papers_data)}\n\n"
-        
+
         for paper_id, paper_info in papers_data.items():
             content += f"## {paper_info['title']}\n"
             content += f"- **Paper ID**: {paper_id}\n"
@@ -183,7 +183,7 @@ def get_topic_papers(topic: str) -> str:
             content += f"- **PDF URL**: [{paper_info['pdf_url']}]({paper_info['pdf_url']})\n\n"
             content += f"### Summary\n{paper_info['summary'][:500]}...\n\n"
             content += "---\n\n"
-        
+
         return content
     except json.JSONDecodeError:
         return f"# Error reading papers data for {topic}\n\nThe papers data file is corrupted."
@@ -191,7 +191,7 @@ def get_topic_papers(topic: str) -> str:
 @mcp.prompt()
 def generate_search_prompt(topic: str, num_papers: int = 5) -> str:
     """Generate a prompt for Claude to find and discuss academic papers on a specific topic."""
-    return f"""Search for {num_papers} academic papers about '{topic}' using the search_papers tool. 
+    return f"""Search for {num_papers} academic papers about '{topic}' using the search_papers tool.
 
 Follow these instructions:
 1. First, search for papers using search_papers(topic='{topic}', max_results={num_papers})
@@ -216,4 +216,4 @@ Please present both detailed information about each paper and a high-level synth
 
 if __name__ == "__main__":
     # Initialize and run the server
-    mcp.run(transport='stdio')
+    mcp.run(transport='stdio')

research_server_L9.py

@@ -18,16 +18,16 @@ mcp = FastMCP("research", port=8001)
 def search_papers(topic: str, max_results: int = 5) -> List[str]:
     """
     Search for papers on arXiv based on a topic and store their information.
-    
+
     Args:
         topic: The topic to search for
         max_results: Maximum number of results to retrieve (default: 5)
-        
+
     Returns:
         List of paper IDs found in the search
     """
-    
-    # Use arxiv to find the papers 
+
+    # Use arxiv to find the papers
     client = arxiv.Client()
 
     # Search for the most relevant articles matching the queried topic
@@ -38,11 +38,11 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
     )
 
     papers = client.results(search)
-    
+
     # Create directory for this topic
     path = os.path.join(PAPER_DIR, topic.lower().replace(" ", "_"))
     os.makedirs(path, exist_ok=True)
-    
+
     file_path = os.path.join(path, "papers_info.json")
 
     # Try to load existing papers info
@@ -52,7 +52,7 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
     except (FileNotFoundError, json.JSONDecodeError):
         papers_info = {}
 
-    # Process each paper and add to papers_info  
+    # Process each paper and add to papers_info
     paper_ids = []
     for paper in papers:
         paper_ids.append(paper.get_short_id())
@@ -64,27 +64,27 @@ def search_papers(topic: str, max_results: int = 5) -> List[str]:
             'published': str(paper.published.date())
         }
         papers_info[paper.get_short_id()] = paper_info
-    
+
     # Save updated papers_info to json file
     with open(file_path, "w") as json_file:
         json.dump(papers_info, json_file, indent=2)
-    
+
     print(f"Results are saved in: {file_path}")
-    
+
     return paper_ids
 
 @mcp.tool()
 def extract_info(paper_id: str) -> str:
     """
     Search for information about a specific paper across all topic directories.
-    
+
     Args:
         paper_id: The ID of the paper to look for
-        
+
     Returns:
         JSON string with paper information if found, error message if not found
     """
- 
+
     for item in os.listdir(PAPER_DIR):
         item_path = os.path.join(PAPER_DIR, item)
         if os.path.isdir(item_path):
@@ -98,7 +98,7 @@ def extract_info(paper_id: str) -> str:
                 except (FileNotFoundError, json.JSONDecodeError) as e:
                     print(f"Error reading {file_path}: {str(e)}")
                     continue
-    
+
     return f"There's no saved information related to paper {paper_id}."
 
 
@@ -107,11 +107,11 @@ def extract_info(paper_id: str) -> str:
 def get_available_folders() -> str:
     """
     List all available topic folders in the papers directory.
-    
+
     This resource provides a simple list of all available topic folders.
     """
     folders = []
-    
+
     # Get all topic directories
     if os.path.exists(PAPER_DIR):
         for topic_dir in os.listdir(PAPER_DIR):
@@ -120,7 +120,7 @@ def get_available_folders() -> str:
                 papers_file = os.path.join(topic_path, "papers_info.json")
                 if os.path.exists(papers_file):
                     folders.append(topic_dir)
-    
+
     # Create a simple markdown list
     content = "# Available Topics\n\n"
     if folders:
@@ -129,31 +129,31 @@ def get_available_folders() -> str:
         content += f"\nUse @{folder} to access papers in that topic.\n"
     else:
         content += "No topics found.\n"
-    
+
     return content
 
 @mcp.resource("papers://{topic}")
 def get_topic_papers(topic: str) -> str:
     """
     Get detailed information about papers on a specific topic.
-    
+
     Args:
         topic: The research topic to retrieve papers for
     """
     topic_dir = topic.lower().replace(" ", "_")
     papers_file = os.path.join(PAPER_DIR, topic_dir, "papers_info.json")
-    
+
     if not os.path.exists(papers_file):
         return f"# No papers found for topic: {topic}\n\nTry searching for papers on this topic first."
-    
+
     try:
         with open(papers_file, 'r') as f:
             papers_data = json.load(f)
-        
+
         # Create markdown content with paper details
         content = f"# Papers on {topic.replace('_', ' ').title()}\n\n"
         content += f"Total papers: {len(papers_data)}\n\n"
-        
+
         for paper_id, paper_info in papers_data.items():
             content += f"## {paper_info['title']}\n"
             content += f"- **Paper ID**: {paper_id}\n"
@@ -162,7 +162,7 @@ def get_topic_papers(topic: str) -> str:
             content += f"- **PDF URL**: [{paper_info['pdf_url']}]({paper_info['pdf_url']})\n\n"
             content += f"### Summary\n{paper_info['summary'][:500]}...\n\n"
             content += "---\n\n"
-        
+
         return content
     except json.JSONDecodeError:
         return f"# Error reading papers data for {topic}\n\nThe papers data file is corrupted."
@@ -170,7 +170,7 @@ def get_topic_papers(topic: str) -> str:
 @mcp.prompt()
 def generate_search_prompt(topic: str, num_papers: int = 5) -> str:
     """Generate a prompt for Claude to find and discuss academic papers on a specific topic."""
-    return f"""Search for {num_papers} academic papers about '{topic}' using the search_papers tool. 
+    return f"""Search for {num_papers} academic papers about '{topic}' using the search_papers tool.
 
     Follow these instructions:
     1. First, search for papers using search_papers(topic='{topic}', max_results={num_papers})
@@ -182,18 +182,24 @@ def generate_search_prompt(topic: str, num_papers: int = 5) -> str:
        - Main contributions or innovations
        - Methodologies used
        - Relevance to the topic '{topic}'
-    
+
     3. Provide a comprehensive summary that includes:
        - Overview of the current state of research in '{topic}'
        - Common themes and trends across the papers
        - Key research gaps or areas for future investigation
        - Most impactful or influential papers in this area
-    
+
     4. Organize your findings in a clear, structured format with headings and bullet points for easy readability.
-    
+
     Please present both detailed information about each paper and a high-level synthesis of the research landscape in {topic}."""
 
 if __name__ == "__main__":
     import os
-    port = int(os.environ.get("PORT", "8000"))  # Render sets PORT for you
-    mcp.run(transport="sse", host="0.0.0.0", port=port)
+
+    # Render donne PORT ; on le recopie dans FASTMCP_PORT
+    port = os.environ.get("PORT", "8000")
+    os.environ.setdefault("FASTMCP_HOST", "0.0.0.0")
+    os.environ["FASTMCP_PORT"] = str(port)
+
+    # Lancement SSE (FastMCP lira host/port via les variables ci-dessus)
+    mcp.run(transport="sse")

server_config.json

@@ -1,6 +1,6 @@
 {
     "mcpServers": {
-        
+
         "filesystem": {
             "command": "npx",
             "args": [
@@ -19,4 +19,3 @@
         }
     }
 }
-  

server_config_L7.json

@@ -1,6 +1,6 @@
 {
     "mcpServers": {
-        
+
         "filesystem": {
             "command": "npx",
             "args": [
@@ -19,4 +19,3 @@
         }
     }
 }
-