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docs(TSP-1091): update MCP server docs for relevance_trigger_agent breaking change #535

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docs(TSP-1091): update MCP server docs for relevance_trigger_agent breaking change #535

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14 changes: 9 additions & 5 deletions integrations/mcp/programmatic-gtm/mcp-server.mdx
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</Accordion>

<Accordion title="ChatGPT" icon="comment">
ChatGPT supports MCP servers through Developer Mode, available on Pro, Team, Enterprise, and Edu plans.

Check warning on line 42 in integrations/mcp/programmatic-gtm/mcp-server.mdx

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Mintlify / Mintlify Validation (relevanceai) - vale-spellcheck

integrations/mcp/programmatic-gtm/mcp-server.mdx#L42 

Did you really mean 'Edu'?

1. Open ChatGPT **Settings**
2. Go to **Connectors** → **Advanced** → **Developer Mode**
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When triggering agents via MCP, you have two execution modes available depending on how long your agent takes to complete.

<Warning>
**Breaking change:** `relevance_trigger_agent` is now asynchronous — it returns a `conversation_id` immediately without waiting for the agent to finish. If you need synchronous (blocking) behavior, use `relevance_trigger_agent_sync` instead. Existing integrations that relied on `relevance_trigger_agent` being synchronous must be updated.
</Warning>

### Execution modes

<Tabs>
<Tab title="Synchronous">
The `relevance_trigger_agent` tool waits for the agent to finish and returns the result directly. It has a 120-second timeout, so use it for agents that complete quickly — single-step agents with minimal tool usage and no workforce nodes.
The `relevance_trigger_agent_sync` tool waits for the agent to finish and returns the result directly. It has a 120-second timeout, so use it for agents that complete quickly — single-step agents with minimal tool usage and no workforce nodes.
</Tab>

<Tab title="Asynchronous">
The `relevance_trigger_agent_async` and `relevance_poll_agent_result` tools work together with no timeout limit. The trigger returns immediately with a conversation ID, which you then poll to check status and retrieve results. Use this for agents with workforce nodes, multi-step chains, external API calls, or any execution expected to exceed 2 minutes.
The `relevance_trigger_agent` and `relevance_poll_agent_result` tools work together with no timeout limit. The trigger returns immediately with a conversation ID, which you then poll to check status and retrieve results. Use this for agents with workforce nodes, multi-step chains, external API calls, or any execution expected to exceed 2 minutes.
</Tab>
</Tabs>

<Warning>
If you encounter timeout errors with `relevance_trigger_agent`, switch to the async pattern. Agents with workforce nodes should always use async execution.
If you encounter timeout errors with `relevance_trigger_agent_sync`, switch to the async pattern. Agents with workforce nodes should always use async execution.
</Warning>

### Async execution workflow

<Steps>
<Step title="Trigger the agent">
Call `relevance_trigger_agent_async` with your agent parameters. This returns immediately with a `conversation_id`.
Call `relevance_trigger_agent` with your agent parameters. This returns immediately with a `conversation_id`.
</Step>

<Step title="Poll for results">
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</Accordion>

<Accordion title="Agent execution timeouts">
Timeout errors from `relevance_trigger_agent` mean your agent exceeded the 120-second synchronous limit. Switch to `relevance_trigger_agent_async` and `relevance_poll_agent_result` instead. See [handling long-running agent executions](#handling-long-running-agent-executions) for the full workflow. Agents with workforce nodes, multi-step chains, or complex workflows should always use the async pattern.
Timeout errors from `relevance_trigger_agent_sync` mean your agent exceeded the 120-second synchronous limit. Switch to `relevance_trigger_agent` and `relevance_poll_agent_result` instead. See [handling long-running agent executions](#handling-long-running-agent-executions) for the full workflow. Agents with workforce nodes, multi-step chains, or complex workflows should always use the async pattern.
</Accordion>
</AccordionGroup>

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