Bring Railway Management
to Google ADK
Learn how to connect Cedar AI to Google ADK and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Cedar AI MCP Server?
Connect your Cedar AI railway management account to any AI agent and simplify how you coordinate rail operations, track car movements, and manage logistics documentation through natural conversation.
What you can do
- Inventory Management — List all railcars currently in your facility and retrieve detailed metadata and status for individual units.
- Car Movement Tracking — Record placements (setouts) and removals (pickups) of railcars at specific locations or tracks.
- Logistics Documentation — List and query waybills to understand shipping instructions, routes, and commodity data.
- Work Order Control — Manage the lifecycle of movement instructions by listing and updating work orders and associated tasks.
- Consist Coordination — Record train arrivals and departures to keep your inventory and operations synchronized.
- Status Maintenance — Update railcar tags and conditions (e.g., Bad Order, Empty/Loaded) directly via AI commands.
How it works
1. Subscribe to this server
2. Enter your Cedar AI API Key (found in your developer settings)
3. Start managing your railway ecosystem from Claude, Cursor, or any MCP client
Who is this for?
- Railroad Operators & Terminal Managers — quickly check yard inventory and record car movements via simple AI queries.
- Logistics Coordinators — monitor waybills and manage work orders across different tracks directly from the workspace.
- Fleet Managers — track railcar statuses and conditions to optimize equipment availability via the AI assistant.
Built-in capabilities (12)
Record train arrival
Record train departure
Get details for a specific railcar
Get details for a specific waybill
Get details for a specific work order
List railcars currently in inventory
List waybills
List work orders
Record removal of cars
Record placement of cars
g., Bad Order, Clean, Loaded/Empty). Update status of a railcar
Update a work order
Why Google ADK?
Google ADK natively supports Cedar AI as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 12 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
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Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Cedar AI
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Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
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Seamless integration with Google Cloud services means you can combine Cedar AI tools with BigQuery, Vertex AI, and Cloud Functions
Cedar AI in Google ADK
Cedar AI and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Cedar AI to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Cedar AI in Google ADK
The Cedar AI MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Cedar AI for Google ADK
Every tool call from Google ADK to the Cedar AI MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I record a railcar movement via AI?
Yes! Use the setout_cars tool to record placement or pickup_cars for removal. Provide the location name and a list of railcar IDs to log the movement instantly.
How do I see the latest waybills for my shipments?
Run the list_waybills query. The agent will retrieve a history of active and completed shipping instructions, including route details and commodity info.
Is it possible to check the status of a specific work order via AI?
Absolutely. Use the get_work_order_details tool with the Work Order ID to retrieve the current status, assigned tasks, and completion progress.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk