Low Risk

query_context

Search the Klever VM knowledge base for smart contract development context. Returns structured JSON with matching entries, scores, and pagination. Use this for precise filtering by type or tags; use search_documentation for human-readable "how do I..." answers.

Risk signalsAccepts freeform code/query input (query)

Part of the Mcp Klever Vm server.

query_context 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 query_context to retrieve information from Mcp Klever Vm 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 query_context 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": {
    "query_context": {}
  }
}

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

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so query_context 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 query_context tool do? +

Search the Klever VM knowledge base for smart contract development context. Returns structured JSON with matching entries, scores, and pagination. Use this for precise filtering by type or tags; use search_documentation for human-readable "how do I..." answers.. It is categorised as a Read tool in the Mcp Klever Vm MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on query_context? +

Register the Mcp Klever Vm MCP server in PolicyLayer and add a rule for query_context: 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 Mcp Klever Vm. Nothing to install.

What risk level is query_context? +

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

Can I rate-limit query_context? +

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

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

query_context is provided by the Mcp Klever Vm MCP server (@klever/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 Mcp Klever Vm tool call.

Deterministic rules across all 16 Mcp Klever Vm tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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