Is the OpenRouteService API free?

Yes. ORS offers a free Standard plan with generous daily limits for all services (directions, isochrones, matrix, geocoding, and optimization). No credit card required. Higher rate limits are available through the Collaborative plan for non-profits, academics, and government organizations.

What routing profiles are supported?

ORS supports driving-car, driving-hgv (heavy goods vehicles), cycling-regular, cycling-road, cycling-mountain, cycling-electric, foot-walking, foot-hiking, and wheelchair. Each profile optimizes routes based on road network restrictions specific to that transportation mode.

Can I solve vehicle routing problems with time windows and capacity constraints?

Yes. The VRP optimization tool uses the VROOM solver. Define jobs with locations, service times, and time windows, then define vehicles with start/end locations, capacities, and operating hours. The solver returns optimized assignments and routes for your entire fleet.

OpenRouteService MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: OpenRouteService
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to OpenRouteService through the Vinkius — pass the Edge URL in the `mcps` parameter and every OpenRouteService tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="OpenRouteService Specialist",
    goal="Help users interact with OpenRouteService effectively",
    backstory=(
        "You are an expert at leveraging OpenRouteService tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in OpenRouteService "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About OpenRouteService MCP Server

Unlock the full power of OpenRouteService from a single conversation. Calculate driving routes, generate reachability maps, solve vehicle routing problems, and geocode addresses — all backed by OpenStreetMap data.

When paired with CrewAI, OpenRouteService becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call OpenRouteService tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Directions — Calculate optimal routes between multiple waypoints for car, bicycle, or pedestrian profiles with distance and duration
Isochrones — Generate reachability polygons showing areas accessible within a given time or distance from any point
Distance Matrix — Compute M×N duration and distance matrices between multiple origins and destinations
VRP Optimization — Solve multi-vehicle routing problems with jobs, vehicles, and capacity constraints using the VROOM solver
Geocoding — Forward and reverse geocode addresses using Pelias, with country boundary filters
GPS Snap — Clean noisy GPS traces by snapping coordinates to the nearest road segment
Elevation — Get altitude data for coordinate sequences using the elevation API

The OpenRouteService MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect OpenRouteService to CrewAI via MCP

Follow these steps to integrate the OpenRouteService MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 10 tools from OpenRouteService

Why Use CrewAI with the OpenRouteService MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with OpenRouteService through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

OpenRouteService + CrewAI Use Cases

Practical scenarios where CrewAI combined with the OpenRouteService MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries OpenRouteService for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries OpenRouteService, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain OpenRouteService tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries OpenRouteService against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

OpenRouteService MCP Tools for CrewAI (10)

These 10 tools become available when you connect OpenRouteService to CrewAI via MCP:

calculate_directions

Identify precise active arrays spanning native Road network points

calculate_isochrones

Inspect deep internal arrays mitigating specific Reachability lines

calculate_matrix

Enumerate explicitly attached structured rules exporting active M * N logs

check_optimization_status

Retrieve explicit Cloud logging tracing explicit Optimization jobs

geocode_search

Identify bounded routing spaces inside the Headless OpenRouteService

get_elevation_line

Provision a highly-available JSON Payload parsing accessible Altitude lines

reverse_geocode

Perform structural extraction of properties driving active OSM boundaries

search_country_boundary

country` fetching strings rigidly ignoring maps spanning outside target ISO boundaries. Irreversibly vaporize explicit validations extracting local search filters

snap_gps_to_road

Retrieve the exact structural matching verifying Map snapping limits

solve_vrp_optimization

Dispatch an automated validation check routing explicit VROOM solvers

Example Prompts for OpenRouteService in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with OpenRouteService immediately.

"Calculate a driving route from Berlin to Munich with estimated time."

"Show me all areas reachable within 15 minutes by car from Times Square."

"Calculate the distance matrix between our 3 warehouses and 5 customer locations."

Troubleshooting OpenRouteService MCP Server with CrewAI

Common issues when connecting OpenRouteService to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

OpenRouteService + CrewAI FAQ

Common questions about integrating OpenRouteService MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.