Low Risk

project_models

Lista todos los modelos de Prisma con sus campos y schema. Útil antes de crear una relación, migration, o Server Action para conocer la estructura exacta de los datos. Args: - schema: filtrar por schema (auth | rbac | audit | base) - model_name: buscar un modelo específico por nombre Returns: mod...

Part of the Project server.

project_models is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call project_models to retrieve information from Project without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though project_models only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "project_models": {}
  }
}

See the full Project policy for all 10 tools.

Get this rule live on your own Project server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access project_models gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so project_models only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the project_models tool do? +

Lista todos los modelos de Prisma con sus campos y schema. Útil antes de crear una relación, migration, o Server Action para conocer la estructura exacta de los datos. Args: - schema: filtrar por schema (auth | rbac | audit | base) - model_name: buscar un modelo específico por nombre Returns: modelos con campos, tipos, relaciones y atributos.. It is categorised as a Read tool in the Project MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on project_models? +

Register the Project MCP server in PolicyLayer and add a rule for project_models: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Project. Nothing to install.

What risk level is project_models? +

project_models is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit project_models? +

Yes. Add a rate_limit block to the project_models rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block project_models completely? +

Set action: deny in the PolicyLayer policy for project_models. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides project_models? +

project_models is provided by the Project MCP server (project-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Project tool call.

Deterministic rules across all 10 Project tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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