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ghl-mcp-server-v2

by zackscriven

ghl_agent_studio_execute

Execute an agent in GoHighLevel and get a complete JSON response. Maintain conversation context using the executionId for session continuity.

Instructions

Execute Agent Executes the specified agent and returns a non-streaming JSON response with the complete agent output. The agent must be in active status and belong to the specified location. locationId is required in the request body.

Session Management:

  • For the first message in a new session, do not include the executionId in the request payload.

  • The API will return an executionId along with the agent response, which uniquely identifies this conversation session.

  • To continue the conversation within the same session, include the executionId from the previous response in subsequent requests. Endpoint: POST /agent-studio/agent/{agentId}/execute (Version header: v3; source: v3/agent-studio-v3.json) OAuth scopes: agent-studio.write

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesRequest body (schema carried verbatim from the official OpenAPI spec).
sourceNo
agentIdYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already show readOnlyHint=false (modifies state) and destructiveHint=false. The description adds session management details but does not elaborate on potential side effects (e.g., agent triggering workflows) beyond stating it executes the agent. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a brief intro, bullet points for session management, and endpoint/scopes info. Every sentence adds value without repetition or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core function and session management adequately but lacks details about the response structure (beyond 'complete agent output'), error conditions, or prerequisites beyond active status. Given no output schema, more detail on the response would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (33%)—only body has a structured description. The description adds value by emphasizing locationId requirements and session management for executionId. However, it does not describe agentId or source, and the nested parameters are mostly handled by the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool executes an agent and returns a non-streaming JSON response. It distinguishes itself from siblings like ghl_agent_studio_create, ghl_agent_studio_get_by_id, and the deprecated execute variant by focusing on execution and session management.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context: agent must be active, locationId required, and session management rules (omit executionId for first message, include for continuation). However, it does not explicitly compare to alternatives or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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