Low Risk

list_solve_tasks

List all available /solve/ task rankings with their top picks. Use this to discover what jobs-to-be-done auxiliar.ai has evaluated installable tools for. Complementary to list_services (cloud services catalog): list_solve_tasks surfaces agent-installable tooling (skills, MCPs, APIs, local binarie...

Part of the Auxiliar server.

list_solve_tasks 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 list_solve_tasks to retrieve information from Auxiliar 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 list_solve_tasks 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": {
    "list_solve_tasks": {}
  }
}

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Get this rule live on your own Auxiliar 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 list_solve_tasks 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 list_solve_tasks 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 list_solve_tasks tool do? +

List all available /solve/ task rankings with their top picks. Use this to discover what jobs-to-be-done auxiliar.ai has evaluated installable tools for. Complementary to list_services (cloud services catalog): list_solve_tasks surfaces agent-installable tooling (skills, MCPs, APIs, local binaries) evaluated on real-world corpora.. It is categorised as a Read tool in the Auxiliar MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on list_solve_tasks? +

Register the Auxiliar MCP server in PolicyLayer and add a rule for list_solve_tasks: 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 Auxiliar. Nothing to install.

What risk level is list_solve_tasks? +

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

Can I rate-limit list_solve_tasks? +

Yes. Add a rate_limit block to the list_solve_tasks 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 list_solve_tasks completely? +

Set action: deny in the PolicyLayer policy for list_solve_tasks. 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 list_solve_tasks? +

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

Enforce policy on every Auxiliar tool call.

Deterministic rules across all 13 Auxiliar tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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