How is this different from connecting Railway MCP directly?

Connected directly, an agent sees every tool the server exposes and holds the credential itself. Through TrustGate you choose which tools each agent gets, and every call is logged against the agent that made it.

What if the Railway MCP API changes?

We track the Railway MCP schema, so the tool catalogue stays current. Tools you have already allowed keep working, and anything new stays denied until you enable it.

Can I give different agents different Railway tools?

Yes. Access is set per agent: one can get a handful of read tools, another the full set. You grant the whole MCP or single tools within it.

Where can I see what my agents did in Railway?

Every call is logged against the agent that made it, with the tool it used. Activity can be sent on to your own monitoring.

Do I need to run the Railway MCP server myself?

No. TrustGate connects to the Railway MCP server and sits in front of it. Your agent only talks to your TrustGate URL, never to Railway directly.

Connect Railway MCP to your AI agents, securely.

Q: Is Railway MCP secure?

The server itself exposes 11 tools, and some of them can write to your Railway account. Behind TrustGate an agent only sees the tools you allow, requests and responses are inspected, and every call is logged. Anything outside the allowlist is denied before it reaches Railway.

One secured endpoint for every Railway call your AI agents make, scoped per user, inspected, and logged.

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What your agents can ask once Railway MCP is connected.

Select the tools your AI agents can call

11 tools from the Railway MCP schema.

Showing 11 tools

whoamireadIdentifies the authenticated Railway user.
list-projectsreadLists the Railway projects available to the authenticated user.
list-servicesreadLists the services inside a project.
create-projectwriteCreates a new Railway project.
list-feature-flagsreadLists the feature flags on a project.
get-feature-flagreadReads a single feature flag.
set-feature-flagwriteSets a feature flag's value, changing runtime behaviour without a deploy.
delete-feature-flaghigh riskDeletes a feature flag. Admin only, and the destructive delete is marked at the protocol level so clients prompt for confirmation.
redeployhigh riskRedeploys a service. Railway names this among the actions to review before approving.
accept-deployhigh riskCommits staged changes and deploys them. Marked destructive, so clients prompt for confirmation.
railway-agenthigh riskHands a natural-language request to Railway's AI agent for multi-step operations such as log analysis, debugging and service configuration.

What Railway MCP exposes

Railway MCP groups its 11 tools into 5 categories, each with a suggested starting policy.

All 11 tools as JSON, ready to paste.

Category	Covers	Access	Suggested policy
Feature Flags	Listing feature flags on a project, reading one, setting its value and deleting it	Read / Write	Setting a flag changes runtime behaviour in production without a deploy; deleting one is admin-only and marked destructive at the protocol level
Projects	Listing projects, creating a project and listing the services inside one	Read / Write	Creating a project starts billable infrastructure
Deployments	Redeploying a service and committing staged changes to deploy them	Read / Write	Both touch running infrastructure and are among the actions Railway names as needing review; accept-deploy is marked destructive so clients prompt for confirmation
Account	Identifying the authenticated user	Read	Safe to allow; useful for confirming which identity the connection is acting as
Agent	Handing a natural-language request to Railway's own AI agent for multi-step operations such as log analysis, debugging and service configuration	Read / Write	A single tool name hides an open-ended multi-step operation that can configure services; Railway lists it among the actions to review before approving

Connect Railway MCP to your AI agent

Four steps, under ten minutes.

01
Sign in to NeuralTrust
Open the NeuralTrust platform, sign in and go to Getting started, then Connect your tools.
02
Choose your agent
When asked which agent you use, pick Claude Code, Codex, Cursor, Windsurf, Copilot or your own code.
03
Connect Railway
Find Railway in the tool list and connect it.
04
Connect your agent
Follow the steps on screen to add the config to your agent, then send the test prompt.

Permissions down to the single tool

You do not allow Railway MCP or block it. You allow the exact tools each agent can call, one by one.

Railway MCP	11 TOOLS AVAILABLE
Code review agent	4 tools, read only
Issue triage bot	9 tools
Platform team assistant	all 11 tools

Tool by toolConnecting the server is not the unit of access. Each tool is granted on its own.
Default denyA tool you have not enabled is never exposed to the agent.
Approval on writesTools that change or delete things can require a human to confirm.

Is Railway MCP secure?

One endpoint instead of raw credentials. Every call is checked against policy and logged.

AI agentsConnect through your MCP client configuration.	NeuralTrustApply controls based on your configuration.	Railway MCP11 documented tools on the hosted server at mcp.railway.com. The local in-process server exposes a different tool set.
Coding assistants	Connection & credentialsper user	Feature Flags4 tools
Internal copilots	Tool access policiesdeny by default	Projects3 tools
Workflow automations	Request & response inspectioninline	Deployments2 tools
Compatible MCP clients	Activity monitoringalerts and logs	All other tools2 tools