Execute a metered API call through the AgentClear proxy. Costs sub-cent per call, charged to your AgentClear wallet.
Accepts raw HTML/template content (payload)
Part of the AgentClear — API Marketplace for AI Agents MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke call_service to trigger processes or run actions in AgentClear — API Marketplace for AI Agents. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
call_service can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
tools:
call_service:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full AgentClear — API Marketplace for AI Agents policy for all 3 tools.
Agents calling execute-class tools like call_service have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
call_service is one of the high-risk operations in AgentClear — API Marketplace for AI Agents. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
Execute a metered API call through the AgentClear proxy. Costs sub-cent per call, charged to your AgentClear wallet.. It is categorised as a Execute tool in the AgentClear — API Marketplace for AI Agents MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Add a rule in your Intercept YAML policy under the tools section for call_service. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the AgentClear — API Marketplace for AI Agents MCP server.
call_service is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the call_service rule in your Intercept 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.
Set action: deny in the Intercept policy for call_service. 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.
call_service is provided by the AgentClear — API Marketplace for AI Agents MCP server (agentclear-ai/mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept