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Glama can run Cloudeval’s MCP server for you. Use its browser chat or connect a compatible client to the hosted server without installing the CLI or Docker on your computer.
Preview — checked 10 September 2026. The Cloudeval server is listed and its build and tool discovery have passed. Glama’s recognition of the existing custom CLI license is still unresolved and can block installation. Authenticated project/report access through Glama, Claude, and ChatGPT has not yet been verified. If installation is unavailable, use direct MCP client setup.
After setup, try this in Glama Chat with Cloudeval selected:

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What runs where

Your chat client asks for a tool. Glama runs the Cloudeval CLI’s MCP process, which uses your Cloudeval key to read permitted account data. Your Cloudeval account and hosted services are still required. The published Glama configuration uses readonly. It can inspect existing project context and reports; it does not start new evaluations. Cloud coverage remains Azure and static AWS CloudFormation evaluation in beta. Hosting does not add live AWS access or broader IaC support.

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Before you begin

  • A Cloudeval account, at least one project you can grant access to, and permission to manage access keys.
  • An existing report in that project for the report example.
  • A Glama account and a private Cloudeval deployment.
  • A hosting plan suitable for ongoing use. The current Glama UI offers one-day ephemeral sandboxes; retaining a stable deployment requires a subscription. Glama hosting charges are separate from Cloudeval charges.
Use a private retained deployment for account data. The Try in Browser sandbox has different privacy terms and is not the place to enter a production Cloudeval key.

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Create a scoped Cloudeval key

  1. Open Developer → Access keys in Cloudeval.
  2. Select Create auth key and choose the MCP Read-only template.
  3. Give it a recognizable name, such as Glama read-only.
  4. Select the project or projects the assistant should read. At least one project is required.
  5. Review the expiry and capabilities. The template defaults to 30 days and includes project, connection, report, download, diagram-export, and MCP access. It does not include billing reads or evaluation runs.
  6. Select Create key, then copy the one-time secret into your private runtime configuration. You cannot retrieve the raw secret again from the key list.
Cloudeval create auth key form showing MCP Read-only, the name Glama read-only, project scope, and a 30-day expiry

Real Cloudeval create-key form with MCP Read-only selected. This capture stops before project selection and key creation; no key was generated.

If Create auth key is unavailable, ask your Cloudeval administrator for the required permission. An IP allowlist, if used, must permit the hosted server’s outbound address, not just your laptop’s address.

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Configure the Glama deployment

  1. Open Cloudeval AI on Glama. Deploy it when installation is available, or open your existing instance under MCP Deployments.
  2. In the instance’s environment section, select Add Environment Variable if the row is missing.
  3. Set the name to CLOUDEVAL_ACCESS_KEY and the value to your own scoped Cloudeval key.
  4. Save the configuration and restart the instance if required. Check that its status becomes started.
These are different credentials. Neither is an Azure or AWS cloud credential. Do not put either secret in a Dockerfile, repository, chat prompt, or public documentation.
Glama deployment help explaining the at-sign server mention, followed by a CLOUDEVAL_ACCESS_KEY environment row with its value masked

Real Glama deployment controls: browser-chat help and the CLOUDEVAL_ACCESS_KEY environment row. The masked value was an unsaved placeholder; the form was discarded after capture.

Glama documents encrypted environment variables and call logging. Review workspace access and logging before using customer data: tool requests and results pass through Glama and your chosen chat provider.

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Use Glama browser chat

  1. Open Glama Chat.
  2. Open the composer’s MCP menu and select Cloudeval AI, or type @ and choose the deployed server. Use its configured instance name if you renamed it.
  3. Send the project-and-report prompt near the top of this page.
  4. Confirm the selected project, report date, and evidence before relying on the answer.
Glama browser chat with the Cloudeval AI MCP server selected and a draft prompt asking for accessible projects and saved reports

Real Glama Chat composer with Cloudeval AI selected. This is an unsent example prompt, not a successful authenticated response.

Expected result after successful authentication: the assistant lists projects allowed by your key, asks which to inspect, and reads a saved report. This is the result to verify, not a captured successful run. A tool list or a started server alone does not prove account access.

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Connect an external client

Open Ingress MCP Connection Profile in your Glama instance. Its Connection URL is the MCP endpoint; the public directory listing URL is not an endpoint. Under Access Tokens, create a Glama token for the connection. Open Install in Client and follow the instructions for your client. Keep the generated configuration private.

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Claude web and Desktop

  1. In Glama’s Install in Client dialog, choose Claude. Choose Claude Code only when configuring that separate CLI product.
  2. Follow Glama’s generated instructions and replace its <ACCESS_TOKEN> placeholder with your Glama token.
  3. In Claude, open Connectors → Add custom connector, enter the generated connection URL, and complete the connection flow. Team or enterprise workspaces may require an owner to add the connector first.
  4. Enable the connector in a conversation and run the verification steps below.
Glama Install in your client dialog with Claude selected and instructions to add a custom connector

Real Glama Install in Client dialog with the Claude tab selected. The private connection URL below the instructions is excluded from this screenshot.

Glama’s current Claude preset embeds the Glama token in the connection URL. Treat the entire URL as a secret. Do not share it in screenshots, support messages, or public install buttons. Follow Claude’s current connector instructions if menu names differ.

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ChatGPT

ChatGPT supports remote MCP apps through developer mode on eligible accounts and workspaces. See OpenAI’s current setup instructions for availability, app creation, and supported authentication. Cloudeval through Glama remains unverified in ChatGPT. The inspected Glama install dialog has no ChatGPT preset. A compatible private authentication flow must be established before this can be presented as a working setup. A Cloudeval key or Glama bearer token is not an OAuth client secret. Do not make an account-data endpoint public to bypass authentication. Once a compatible connection is available, create a custom MCP app with that endpoint, finish authentication, scan the tools, select the app in a conversation, and run the checks below. Until then, use Glama Chat or direct MCP setup in a supported local client.

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Cursor, VS Code, Codex, and Claude Code

Glama provides separate presets for these clients. Use the generated command or configuration for your own instance and Glama token. You do not need a local Docker container when the client connects to Glama’s remote endpoint.

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Verify account access

Run these checks in order through your selected client:
  1. capabilities_get: confirm the server responds and exposes the expected toolset.
  2. identity_get: confirm authentication succeeds with the intended scoped identity.
  3. projects_list: confirm only the projects permitted by the key are available.
  4. Select one returned project, then use reports_list and an appropriate report tool such as reports_waf to inspect a saved report.
Stop if the account, scope, or project is unexpected. The discovery check was verified for the published build; the authenticated checks above are still pending for this hosted guide. Screenshots show actual setup controls, not a successful customer-data session.

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Common mistakes

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Rotate or revoke access

Create a replacement scoped key in Cloudeval, update the Glama environment, restart and verify the connection, then revoke the old key from Developer → Access keys. Revoke the old Glama token separately if you are replacing the external client’s connection. Removing a connector from a chat client does not revoke its Cloudeval key.
Last modified on September 9, 2026