Optimize route data JSON for context window efficiency

Refactor route data pipeline to reduce JSON size from ~5000 to ~200 characters:
- Move image generation to get_route_data() using full geometry for quality
- Extract route image utilities to separate route_utils.py module
- Update generate_route_image() to load pre-generated images with optional custom titles
- Remove coordinate arrays from JSON, replaced with temporary image file paths
- Update app.py interface descriptions to reflect new workflow

This optimization significantly reduces MCP server context window usage while maintaining full route visualization capabilities.

.gitignore

@@ -1,3 +1,4 @@
 .env
 .idea
-__pycache__
+__pycache__
+.claude/*

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
-from tools import get_coords_from_address, calculate_distance, get_route_details
+from tools import get_coords_from_address, calculate_direct_distance, get_route_data, extract_route_time, \
+    extract_route_distance, generate_route_image
 
 # --- Tools ---
 geocoding_interface = gr.Interface(
@@ -15,7 +16,7 @@ geocoding_interface = gr.Interface(
 )
 
 distance_interface = gr.Interface(
-    fn=calculate_distance,
+    fn=calculate_direct_distance,
     inputs=[
         gr.Number(label="Latitude Point A"),
         gr.Number(label="Longitude Point A"),
@@ -31,7 +32,7 @@ distance_interface = gr.Interface(
 )
 
 route_planner_interface = gr.Interface(
-    fn=get_route_details,
+    fn=get_route_data,
     inputs=[
         gr.Number(label="Start Latitude"),
         gr.Number(label="Start Longitude"),
@@ -43,7 +44,34 @@ route_planner_interface = gr.Interface(
         gr.Textbox(label="Route Details")
     ],
     title="Route Planner",
-    description="A tool to calculate real-world route distance and travel time."
+    description="Get optimized route data with pre-generated map image for visualization."
+)
+
+extract_time_interface = gr.Interface(
+    fn=extract_route_time,
+    inputs=gr.Textbox(label="Route Data (JSON)", lines=3),
+    outputs=gr.Textbox(label="Travel Time"),
+    title="Extract Route Time",
+    description="Extract human-readable travel time from route data"
+)
+
+extract_distance_interface = gr.Interface(
+    fn=extract_route_distance,
+    inputs=gr.Textbox(label="Route Data (JSON)", lines=3),
+    outputs=gr.Textbox(label="Distance"),
+    title="Extract Route Distance",
+    description="Extract distance in km from route data"
+)
+
+route_map_interface = gr.Interface(
+    fn=generate_route_image,
+    inputs=[
+        gr.Textbox(label="Route Data (JSON)", lines=3),
+        gr.Textbox(label="Custom Title (Optional)", placeholder="e.g., My Route to Work")
+    ],
+    outputs="image",
+    title="Generate Route Map",
+    description="Extract route image and optionally add custom title overlay."
 )
 
 # --- About Tab ---
@@ -57,9 +85,26 @@ with gr.Blocks() as about_tab:
 
     ## Available Tools
 
-    - **Address Geocoding**: Converts a physical address into latitude and longitude coordinates.
-    - **Distance Calculator**: Calculates the distance between two sets of coordinates.
-    - **Travel Time Estimator**: Estimates travel time based on distance and mode of transport.
+    ### 📍 Location Tools
+    - **Address Geocoding**: Converts a physical address into latitude and longitude coordinates
+    
+    ### 📏 Distance Tools  
+    - **Distance Calculator**: Calculates straight-line distance between two coordinates
+    - **Extract Route Distance**: Extracts the actual travel distance from route data
+    
+    ### 🚗 Route Planning
+    - **Route Planner**: Gets complete route data including geometry, distance and duration for car/walk/bike
+    - **Extract Route Time**: Extracts human-readable travel time from route data (e.g., "15 min", "1 h 23 min")
+    
+    ### 🗺️ Visualization
+    - **Generate Route Map**: Extracts pre-generated route image with optional custom title overlay
+    
+    ## Usage
+    These tools are designed to work together. For example:
+    1. Use Address Geocoding to get coordinates
+    2. Use Route Planner to get route data
+    3. Use Extract tools to get specific metrics
+    4. Use Generate Route Map to visualize the route
     
     ## If you have any questions or feedback, please don't hesitate to reach me.
 
@@ -72,8 +117,10 @@ with gr.Blocks() as about_tab:
 
 # --- Assemble the Tabbed Interface ---
 demo = gr.TabbedInterface(
-    [about_tab, geocoding_interface, distance_interface, route_planner_interface],
-    ["About", "Address Geocoding", "Distance Calculator", "Route Planner"],
+    [about_tab, geocoding_interface, distance_interface, route_planner_interface,
+     extract_time_interface, extract_distance_interface, route_map_interface],
+    ["About", "Address Geocoding", "Distance Calculator", "Route Planner",
+     "Extract Time", "Extract Distance", "Route Map"],
     title="🌍 Geocalc MCP Server"
 )
 

pyproject.toml

@@ -8,7 +8,11 @@ dependencies = [
     "aiohttp>=3.12.9",
     "geopy>=2.4.1",
     "gradio>=5.33.0",
+    "matplotlib>=3.10.3",
     "mcp>=1.9.3",
     "openrouteservice>=2.3.3",
+    "pillow<10.0.0",
+    "polyline>=2.0.2",
+    "py-staticmaps>=0.4.0",
     "python-dotenv>=1.1.0",
 ]

requirements.txt

@@ -17,6 +17,8 @@ anyio==4.9.0
     #   mcp
     #   sse-starlette
     #   starlette
+appdirs==1.4.4
+    # via py-staticmaps
 attrs==25.3.0
     # via aiohttp
 certifi==2025.4.26
@@ -30,12 +32,18 @@ click==8.2.1
     # via
     #   typer
     #   uvicorn
+contourpy==1.3.2
+    # via matplotlib
+cycler==0.12.1
+    # via matplotlib
 fastapi==0.115.12
     # via gradio
 ffmpy==0.6.0
     # via gradio
 filelock==3.18.0
     # via huggingface-hub
+fonttools==4.58.2
+    # via matplotlib
 frozenlist==1.6.2
     # via
     #   aiohttp
@@ -44,8 +52,12 @@ fsspec==2025.5.1
     # via
     #   gradio-client
     #   huggingface-hub
+future==1.0.0
+    # via s2sphere
 geographiclib==2.0
-    # via geopy
+    # via
+    #   geopy
+    #   py-staticmaps
 geopy==2.4.1
     # via geocalc-mcp (pyproject.toml)
 gradio==5.33.0
@@ -82,12 +94,16 @@ idna==3.10
     #   yarl
 jinja2==3.1.6
     # via gradio
+kiwisolver==1.4.8
+    # via matplotlib
 markdown-it-py==3.0.0
     # via rich
 markupsafe==3.0.2
     # via
     #   gradio
     #   jinja2
+matplotlib==3.10.3
+    # via geocalc-mcp (pyproject.toml)
 mcp==1.9.3
     # via geocalc-mcp (pyproject.toml)
 mdurl==0.1.2
@@ -98,7 +114,9 @@ multidict==6.4.4
     #   yarl
 numpy==2.2.6
     # via
+    #   contourpy
     #   gradio
+    #   matplotlib
     #   pandas
 openrouteservice==2.3.3
     # via geocalc-mcp (pyproject.toml)
@@ -109,14 +127,23 @@ packaging==25.0
     #   gradio
     #   gradio-client
     #   huggingface-hub
+    #   matplotlib
 pandas==2.3.0
     # via gradio
-pillow==11.2.1
-    # via gradio
+pillow==9.5.0
+    # via
+    #   geocalc-mcp (pyproject.toml)
+    #   gradio
+    #   matplotlib
+    #   py-staticmaps
+polyline==2.0.2
+    # via geocalc-mcp (pyproject.toml)
 propcache==0.3.1
     # via
     #   aiohttp
     #   yarl
+py-staticmaps==0.4.0
+    # via geocalc-mcp (pyproject.toml)
 pydantic==2.11.5
     # via
     #   fastapi
@@ -131,8 +158,12 @@ pydub==0.25.1
     # via gradio
 pygments==2.19.1
     # via rich
+pyparsing==3.2.3
+    # via matplotlib
 python-dateutil==2.9.0.post0
-    # via pandas
+    # via
+    #   matplotlib
+    #   pandas
 python-dotenv==1.1.0
     # via
     #   geocalc-mcp (pyproject.toml)
@@ -141,6 +172,8 @@ python-multipart==0.0.20
     # via
     #   gradio
     #   mcp
+python-slugify==8.0.4
+    # via py-staticmaps
 pytz==2025.2
     # via pandas
 pyyaml==6.0.2
@@ -151,10 +184,13 @@ requests==2.32.3
     # via
     #   huggingface-hub
     #   openrouteservice
+    #   py-staticmaps
 rich==14.0.0
     # via typer
 ruff==0.11.13
     # via gradio
+s2sphere==0.2.5
+    # via py-staticmaps
 safehttpx==0.1.6
     # via gradio
 semantic-version==2.10.0
@@ -172,6 +208,10 @@ starlette==0.46.2
     #   fastapi
     #   gradio
     #   mcp
+svgwrite==1.4.3
+    # via py-staticmaps
+text-unidecode==1.3
+    # via python-slugify
 tomlkit==0.13.3
     # via gradio
 tqdm==4.67.1

route_utils.py

@@ -0,0 +1,77 @@
+import os
+import uuid
+import tempfile
+import staticmaps
+from PIL import Image
+
+
+TEMP_DIR = tempfile.mkdtemp(prefix="geocalc_")
+
+
+def generate_route_image_file(coords, start_lat, start_lon, end_lat, end_lon):
+    """Generate route image and save to temp file."""
+    context = staticmaps.Context()
+    context.set_tile_provider(staticmaps.tile_provider_OSM)
+    
+    # Create route line
+    line = staticmaps.Line(
+        [staticmaps.create_latlng(lat, lng) for lat, lng in coords],
+        color=staticmaps.BLUE,
+        width=4
+    )
+    context.add_object(line)
+    
+    # Add start marker (green)
+    start_marker = staticmaps.Marker(
+        staticmaps.create_latlng(start_lat, start_lon),
+        color=staticmaps.GREEN,
+        size=12
+    )
+    context.add_object(start_marker)
+    
+    # Add end marker (red)
+    end_marker = staticmaps.Marker(
+        staticmaps.create_latlng(end_lat, end_lon),
+        color=staticmaps.RED,
+        size=12
+    )
+    context.add_object(end_marker)
+    
+    # Generate image and save to temp file
+    image = context.render_pillow(800, 600)
+    
+    # Create unique temp file path
+    filename = f"route_{uuid.uuid4().hex[:8]}.png"
+    filepath = os.path.join(TEMP_DIR, filename)
+    
+    image.save(filepath)
+    return filepath
+
+
+def load_image_with_title(image_path, custom_title=None):
+    """Load image from path and optionally add custom title."""
+    image = Image.open(image_path)
+    
+    if custom_title:
+        from PIL import ImageDraw, ImageFont
+        draw = ImageDraw.Draw(image)
+        
+        # Try to use a nice font, fallback to default
+        try:
+            font = ImageFont.truetype("Arial.ttf", 24)
+        except:
+            font = ImageFont.load_default()
+        
+        # Add title at top center
+        text_bbox = draw.textbbox((0, 0), custom_title, font=font)
+        text_width = text_bbox[2] - text_bbox[0]
+        x = (image.width - text_width) // 2
+        y = 10
+        
+        # Add background rectangle for better readability
+        padding = 5
+        draw.rectangle([x-padding, y-padding, x+text_width+padding, y+text_bbox[3]+padding], 
+                      fill="white", outline="black")
+        draw.text((x, y), custom_title, fill="black", font=font)
+    
+    return image

tools.py

@@ -1,11 +1,18 @@
+import json
+import matplotlib.pyplot as plt
+import polyline
+from PIL import Image
+from io import BytesIO
 from geopy.geocoders import Nominatim
 from geopy import distance
 import openrouteservice
 from openrouteservice.exceptions import ApiError
 import os
 from dotenv import load_dotenv
+from route_utils import generate_route_image_file, load_image_with_title
 
 load_dotenv()
+ORS_API_KEY = os.getenv("ORS_API_KEY")
 
 
 def get_coords_from_address(address: str) -> str:
@@ -37,7 +44,7 @@ def get_coords_from_address(address: str) -> str:
         return "An error occurred while trying to contact the geocoding service."
 
 
-def calculate_distance(lat1: float, lon1: float, lat2: float, lon2: float, unit: str = "km") -> str:
+def calculate_direct_distance(lat1: float, lon1: float, lat2: float, lon2: float, unit: str = "km") -> str:
     """
     Calculates the distance between two points on the Earth's surface using the Haversine formula.
 
@@ -49,20 +56,21 @@ def calculate_distance(lat1: float, lon1: float, lat2: float, lon2: float, unit:
         unit (str, optional): Unit of measurement for the distance. Default is "km".
 
     Returns:
-        float: The distance between the two points in kilometers.
+        str: The distance between the two points in kilometers.
     """
 
     print("calculate_distance", lat1, lon1, lat2, lon2, unit)
     if unit == "km":
-        return distance.distance((lat1, lon1), (lat2, lon2)).km
+        return str(round(distance.distance((lat1, lon1), (lat2, lon2)).km, 2))
     else:
-        return distance.distance((lat1, lon1), (lat2, lon2)).miles
+        return str(round(distance.distance((lat1, lon1), (lat2, lon2)).miles, 2))
 
 
 # This is now a standard, synchronous function
-def get_route_details(start_lat: float, start_lon: float, end_lat: float, end_lon: float, mode: str) -> str:
+def get_route_data(start_lat: float, start_lon: float, end_lat: float, end_lon: float, mode: str) -> str:
     """
-    Calculates route distance and duration using the OpenRouteService API.
+    Fetches optimized route data from the OpenRouteService API for a given start/end point and travel mode.
+    This is the primary data-gathering tool. Its output is a compact JSON string meant to be used by other tools.
 
     Args:
         start_lat (float): Latitude of the starting point.
@@ -72,7 +80,7 @@ def get_route_details(start_lat: float, start_lon: float, end_lat: float, end_lo
         mode (str): The mode of transportation (e.g., "car", "walk", "bike").
 
     Returns:
-        str: A string containing the route distance and duration.
+        A compact JSON string containing optimized route details with decoded coordinates.
     """
     profile_map = {
         "car": "driving-car",
@@ -81,33 +89,106 @@ def get_route_details(start_lat: float, start_lon: float, end_lat: float, end_lo
     }
 
     if mode not in profile_map:
-        return "Invalid mode. Please use 'car', 'walk', or 'bike'."
+        return json.dumps({"error": "Invalid mode. Please use 'car', 'walk', or 'bike'."})
 
-    ORS_API_KEY = os.getenv("ORS_API_KEY")
     client_ors = openrouteservice.Client(key=ORS_API_KEY)
-
     coords = ((start_lon, start_lat), (end_lon, end_lat))
 
     try:
-        # Call the directions API
-        routes = client_ors.directions(
-            coordinates=coords,
-            profile=profile_map[mode],
-        )
+        routes = client_ors.directions(coordinates=coords, profile=profile_map[mode], geometry='true')
+        route_data = routes['routes'][0]
 
-        # Extract summary data from the response
-        summary = routes['routes'][0]['summary']
-        print("get_route_details summary:", summary)
-        distance_km = round(summary['distance'] / 1000, 1)  # Distance in meters
-        duration_sec = summary['duration']  # Duration in seconds
+        # Decode full polyline geometry for image generation
+        decoded_coords = polyline.decode(route_data['geometry'])
 
-        # Format the duration into hours and minutes
-        hours = int(duration_sec // 3600)
-        minutes = int((duration_sec % 3600) // 60)
+        # Generate route image with full detail
+        image_path = generate_route_image_file(decoded_coords, start_lat, start_lon, end_lat, end_lon)
 
-        return f"The route by {mode} is {distance_km} km and will take approximately {hours} hours and {minutes} minutes."
+        # Return optimized JSON with image path
+        optimized_data = {
+            "summary": route_data['summary'],
+            "map_image_path": image_path,
+            "start_point": [start_lat, start_lon],
+            "end_point": [end_lat, end_lon]
+        }
 
+        return json.dumps(optimized_data)
     except ApiError as e:
-        return f"Could not find a route. API Error: {e}"
+        return json.dumps({"error": f"Could not find a route. API Error: {e}"})
     except Exception as e:
-        return f"An unexpected error occurred: {e}"
+        return json.dumps({"error": f"An unexpected error occurred: {e}"})
+
+
+def extract_route_time(route_json: str) -> str:
+    """
+    Extract travel time from route data.
+
+    Args:
+        route_json (str): JSON string containing route data
+
+    Returns:
+        Time in human format like '15 min' or '1 h 23 min'
+    """
+    data = json.loads(route_json)
+    if "error" in data:
+        return data["error"]
+
+    seconds = data['summary']['duration']
+    minutes = int(seconds / 60)
+
+    if minutes < 60:
+        return f"{minutes} min"
+    else:
+        hours = minutes // 60
+        mins = minutes % 60
+        return f"{hours} h {mins} min"
+
+
+def extract_route_distance(route_json: str) -> str:
+    """
+    Extract distance from route data.
+
+    Args:
+        route_json (str): JSON string containing route data
+    Returns:
+         Distance like '5.2 km'
+    """
+    data = json.loads(route_json)
+    print("extract_route_distance", data)
+    if "error" in data:
+        return data["error"]
+
+    meters = data['summary']['distance']
+    km = round(meters / 1000, 1)
+    return f"{km} km"
+
+
+def generate_route_image(route_json: str, custom_title: str = None) -> Image.Image:
+    """
+    Extract route image from JSON data and optionally add custom title.
+
+    Args:
+        route_json (str): JSON string containing route data
+        custom_title (str): Optional title to add to the image
+
+    Returns:
+        PIL.Image.Image: The generated route image
+    """
+    data = json.loads(route_json)
+
+    if "error" in data:
+        # Create error image
+        fig, ax = plt.subplots(1, 1, figsize=(8, 6))
+        ax.text(0.5, 0.5, f"Error: {data['error']}",
+                ha='center', va='center', fontsize=12, color='red')
+        ax.axis('off')
+        buf = BytesIO()
+        fig.savefig(buf, format='png', dpi=150, bbox_inches='tight')
+        buf.seek(0)
+        img = Image.open(buf)
+        plt.close(fig)
+        return img
+
+    # Load image from path and add title if provided
+    image_path = data['map_image_path']
+    return load_image_with_title(image_path, custom_title)

uv.lock

@@ -127,6 +127,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a1/ee/48ca1a7c89ffec8b6a0c5d02b89c305671d5ffd8d3c94acf8b8c408575bb/anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c", size = 100916 },
 ]
 
+[[package]]
+name = "appdirs"
+version = "1.4.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/d7/d8/05696357e0311f5b5c316d7b95f46c669dd9c15aaeecbb48c7d0aeb88c40/appdirs-1.4.4.tar.gz", hash = "sha256:7d5d0167b2b1ba821647616af46a749d1c653740dd0d2415100fe26e27afdf41", size = 13470 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/3b/00/2344469e2084fb287c2e0b57b72910309874c3245463acd6cf5e3db69324/appdirs-1.4.4-py2.py3-none-any.whl", hash = "sha256:a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128", size = 9566 },
+]
+
 [[package]]
 name = "attrs"
 version = "25.3.0"
@@ -254,6 +263,69 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335 },
 ]
 
+[[package]]
+name = "contourpy"
+version = "1.3.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/66/54/eb9bfc647b19f2009dd5c7f5ec51c4e6ca831725f1aea7a993034f483147/contourpy-1.3.2.tar.gz", hash = "sha256:b6945942715a034c671b7fc54f9588126b0b8bf23db2696e3ca8328f3ff0ab54", size = 13466130 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/b3/b9/ede788a0b56fc5b071639d06c33cb893f68b1178938f3425debebe2dab78/contourpy-1.3.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6a37a2fb93d4df3fc4c0e363ea4d16f83195fc09c891bc8ce072b9d084853445", size = 269636 },
+    { url = "https://files.pythonhosted.org/packages/e6/75/3469f011d64b8bbfa04f709bfc23e1dd71be54d05b1b083be9f5b22750d1/contourpy-1.3.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:b7cd50c38f500bbcc9b6a46643a40e0913673f869315d8e70de0438817cb7773", size = 254636 },
+    { url = "https://files.pythonhosted.org/packages/8d/2f/95adb8dae08ce0ebca4fd8e7ad653159565d9739128b2d5977806656fcd2/contourpy-1.3.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d6658ccc7251a4433eebd89ed2672c2ed96fba367fd25ca9512aa92a4b46c4f1", size = 313053 },
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