RUBE_MULTI_EXECUTE_TOOL

// WHEN AI AGENTS USE THIS TOOL

AI agents invoke RUBE_MULTI_EXECUTE_TOOL to trigger processes or run actions in Rube. 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.

// WHY ENFORCE A POLICY ON RUBE_MULTI_EXECUTE_TOOL

RUBE_MULTI_EXECUTE_TOOL 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.

// RECOMMENDED POLICY

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

composio-rube.yaml

tools:
  RUBE_MULTI_EXECUTE_TOOL:
    rules:
      - action: allow
        rate_limit:
          max: 10
          window: 60
        validate:
          required_args: true

See the full Rube policy for all 11 tools.

// DETAILS

Tool Name RUBE_MULTI_EXECUTE_TOOL

Category Execute

MCP Server Rube MCP Server

Risk Level High

// MORE RUBE TOOLS

Destructive RUBE_REMOTE_WORKBENCH Execute RUBE_EXECUTE_RECIPE Execute RUBE_REMOTE_BASH_TOOL Write RUBE_CREATE_UPDATE_RECIPE Write RUBE_MANAGE_CONNECTIONS Write RUBE_MANAGE_RECIPE_SCHEDULE Read RUBE_FIND_RECIPE Read RUBE_GET_RECIPE_DETAILS

View all 11 tools →

// WHAT CAN GO WRONG

Agents calling execute-class tools like RUBE_MULTI_EXECUTE_TOOL have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

// OTHER EXECUTE TOOLS ACROSS MCP SERVERS

Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

Agent Passport System — Cryptographic Identity for AI Agents commerce_preflight Agent Passport System — Cryptographic Identity for AI Agents execute_with_context Agent Passport System — Cryptographic Identity for AI Agents gateway_execute_approval Agent Passport System — Cryptographic Identity for AI Agents governance_360 Agent Passport System — Cryptographic Identity for AI Agents parse_governance_block_html AgentClear — API Marketplace for AI Agents call_service

// IN CONTEXT OF HIGH RISK

RUBE_MULTI_EXECUTE_TOOL is one of the high-risk operations in Rube. 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.

// RELATED READING

// FAQ

What does the RUBE_MULTI_EXECUTE_TOOL tool do? +

Fast and parallel tool executor for tools and recipes discovered through RUBE_SEARCH_TOOLS. Use this tool to execute up to 50 tools in parallel across apps. Response contains structured outputs ready for immediate analysis - avoid reprocessing them via remote bash/workbench tools. Prerequisites: - Always use valid tool slugs and their arguments discovered through RUBE_SEARCH_TOOLS. NEVER invent tool slugs or argument fields. ALWAYS pass STRICTLY schema-compliant arguments with each tool execution. - Ensure an ACTIVE connection exists for the toolkits that are going to be executed. If none exists, MUST initiate one via RUBE_MANAGE_CONNECTIONS before execution. - Only batch tools that are logically independent - no required ordering or dependencies between tools or their outputs. DO NOT pass dummy or placeholder values; always resolve required inputs using appropriate tools first. Usage guidelines: - Use this whenever a tool is discovered and has to be called, either as part of a multi-step workflow or as a standalone tool. - If RUBE_SEARCH_TOOLS returns a tool that can perform the task, prefer calling it via this executor. Do not write custom API calls or ad-hoc scripts for tasks that can be completed by available Composio tools. - Prefer parallel execution: group independent tools into a single multi-execute call where possible. - Predictively set sync_response_to_workbench=true if the response may be large or needed for later scripting. It still shows response inline; if the actual response data turns out small and easy to handle, keep everything inline and SKIP workbench usage. - Responses contain structured outputs for each tool. RULE: Small data - process yourself inline; large data - process in the workbench. - ALWAYS include inline references/links to sources in MARKDOWN format directly next to the relevant text. Eg provide slack thread links alongside with summary, render document links instead of raw IDs. Restrictions: Some tools or toolkits may be disabled in this environment. If the response indicates a restriction, inform the user and STOP execution immediately. Do NOT attempt workarounds or speculative actions. - CRITICAL: You MUST always include the 'memory' parameter - never omit it. Even if you think there's nothing to remember, include an empty object {} for memory. Memory Storage: - CRITICAL FORMAT: Memory must be a dictionary where keys are app names (strings) and values are arrays of strings. NEVER pass nested objects or dictionaries as values. - CORRECT format: {"slack": ["Channel general has ID C1234567"], "gmail": ["John's email is john@example.com"]} - Write memory entries in natural, descriptive language - NOT as key-value pairs. Use full sentences that clearly describe the relationship or information. - ONLY store information that will be valuable for future tool executions - focus on persistent data that saves API calls. - STORE: ID mappings, entity relationships, configs, stable identifiers. - DO NOT STORE: Action descriptions, temporary status updates, logs, or "sent/fetched" confirmations. - Examples of GOOD memory (store these): * "The important channel in Slack has ID C1234567 and is called #general" * "The team's main repository is owned by user 'teamlead' with ID 98765" * "The user prefers markdown docs with professional writing, no emojis" (user_preference) - Examples of BAD memory (DON'T store these): * "Successfully sent email to john@example.com with message hi" * "Fetching emails from last day (Sep 6, 2025) for analysis" - Do not repeat the memories stored or found previously. . It is categorised as a Execute tool in the Rube MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on RUBE_MULTI_EXECUTE_TOOL? +

Add a rule in your Intercept YAML policy under the tools section for RUBE_MULTI_EXECUTE_TOOL. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Rube MCP server.

What risk level is RUBE_MULTI_EXECUTE_TOOL? +

RUBE_MULTI_EXECUTE_TOOL is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit RUBE_MULTI_EXECUTE_TOOL? +

Yes. Add a rate_limit block to the RUBE_MULTI_EXECUTE_TOOL 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.

How do I block RUBE_MULTI_EXECUTE_TOOL completely? +

Set action: deny in the Intercept policy for RUBE_MULTI_EXECUTE_TOOL. 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 RUBE_MULTI_EXECUTE_TOOL? +

RUBE_MULTI_EXECUTE_TOOL is provided by the Rube MCP server (Composio/Rube). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on Rube