Leverly

@leverly show me all active reattempts from the last 24 hours so I can see which leads are stuck in retry loops

Here's a summary of active reattempts in the last 24 hours: 8 leads are currently in retry cycles. The most frequent is reattempt ID 'ra_4f8e2a' for lead 'john.doe@example.com' (12 attempts since 6:30 AM). Three others have exceeded 5 attempts: 'ra_9b3c1d' (lead 'jane.smith@corp.net', 7 attempts), 'ra_2e7f4a' (lead 'mike.jones@startup.io', 6 attempts), and 'ra_5d1c8b' (lead 'sarah.lee@agency.com', 5 attempts). The remaining 4 are under 3 attempts each. All are retrying due to webhook delivery failures to your CRM endpoint.

This example shows the List Reattempts tool's ability to surface ingestion bottlenecks. Useful when diagnosing lead delivery issues. Note that the tool returns raw reattempt metadata—you'll need to cross-reference lead IDs with your CRM to understand business impact. Requires API key with read access to reattempt logs.

@leverly stop reattempts for ID ra_4f8e2a immediately—we've confirmed that lead's webhook endpoint is permanently down

Reattempts for ID 'ra_4f8e2a' have been stopped. This lead (john.doe@example.com) had 12 pending retry attempts scheduled over the next 6 hours. All queued retries are now canceled. The lead record remains in your Leverly account, but no further delivery attempts will be made to the failed webhook endpoint. If you fix the endpoint later, you'll need to manually re-trigger ingestion for this lead or wait for a new submission.

This demonstrates the Stop Leverly Reattempts tool's side-effect: halting retries is permanent for that reattempt cycle. Use this when you've diagnosed the root cause (bad endpoint, duplicate lead, etc.) and want to prevent unnecessary API load. Stopping reattempts does NOT delete the lead—it only cancels pending delivery attempts. Requires API key with write access.

@leverly check all reattempts and recommend which ones I should stop based on attempt count and time elapsed since first failure

I reviewed all active reattempts and identified 3 candidates for stopping: (1) 'ra_4f8e2a' has 12 attempts over 18 hours—likely a persistent endpoint issue, not a transient network blip. (2) 'ra_9b3c1d' has 7 attempts in 14 hours with identical 503 errors—suggests your CRM is rejecting this lead format. (3) 'ra_2e7f4a' has 6 attempts but the lead email domain bounced in your email tool yesterday—probably invalid. I recommend stopping these three to reduce retry noise. The other 5 reattempts are under 4 attempts and started within the last 3 hours, so they may resolve naturally.

This synthesis example pairs Leverly's reattempt data with the AI's pattern-matching to triage action items. The AI can't access your CRM or email tool directly (unless you've connected those MCPs too), so cross-system insights here are illustrative. In practice, you'd confirm the AI's reasoning before stopping reattempts. Requires read access; stopping would need a follow-up command.

Stop broken lead retries before they flood your CRM

A 6-person sales team runs paid ads that push leads into Leverly for instant routing. When a webhook misconfiguration sends bad data, Leverly retries the ingestion dozens of times, creating duplicate records and alert fatigue. This MCP is the fix: one agent lists active reattempts, spots the pattern (same lead ID failing repeatedly), and stops the loop with a single command. It works because the tool set is narrow—two actions that map directly to the failure mode. If your team sees fewer than five routing failures per week, manual cleanup in the Leverly dashboard is faster. Use this MCP when automation prevents the mess from reaching your CRM in the first place.

When reattempt history reveals integration gaps

A 3-person growth team wraps a webinar campaign and wants to confirm every lead made it into Salesforce. They ask an agent to list Leverly reattempts from the past 48 hours. The output shows twelve leads stuck in retry loops because the Salesforce API rate limit was hit. The team stops the reattempts, batches the leads manually, and updates their integration logic. This scenario works because the MCP exposes the failure log without requiring dashboard access or CSV exports. The trade-off: if your campaigns generate thousands of leads per day, the list tool returns too much noise to parse quickly. This MCP shines for teams running 10-50 campaigns per month who need spot-check visibility into routing health.

Diagnose lead delivery complaints in under two minutes

A solo customer success manager fields a ticket: a client claims their lead never arrived. The CSM asks an agent to list Leverly reattempts for the client's account ID in the past hour. The agent finds the lead stuck in a retry loop due to an expired API key on the client's end. The CSM stops the reattempt, notifies the client, and closes the ticket. This scenario is the MCP's strongest fit—two tools, one clear diagnostic path, no ambiguity. The limitation: if your support volume exceeds 20 tickets per day, you need a dedicated Leverly integration with richer search and filtering. For small teams handling occasional escalations, this MCP turns a 15-minute dashboard hunt into a 90-second Slack exchange.