outbound_sequencer
Séquences outbound — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub → CFO + CRO B2B SaaS France — Séquence 6 touches multi-canal · Taux réponse +180%. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/outbound-sequencer.md
What outbound_sequencer does on Mcp Knowledge
AI agents use outbound_sequencer to create or update resources in Mcp Knowledge, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Knowledge environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
icp | object | Yes | |
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
offer | object | Yes | |
excludedAngles | string | — | |
targetAccounts | array | — |
Parameters from the server's own tool schema.
Why outbound_sequencer is rated Medium
The tool generates and likely dispatches or schedules outbound sales sequences (multi-channel, 6-touch cadences targeting C-suite contacts). This constitutes creating/writing structured outreach content and potentially triggering external communications.
From the tool's definition Séquences outbound — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Séquence 6 touches multi-canal
Risk signalsHigh parameter count (12 properties)
Attacks that exploit this kind of access
The rule that runs outbound_sequencer safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For outbound_sequencer, this is the rule to start with:
outbound_sequencer stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every outbound_sequencer call is checked against it from then on.
Questions about outbound_sequencer
Séquences outbound — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub → CFO + CRO B2B SaaS France — Séquence 6 touches multi-canal · Taux réponse +180%. Inputs are validated server-side — send the documented case fields. It is categorised as a Write tool in the Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
outbound_sequencer accepts 5 parameters: icp, async, offer, excludedAngles, targetAccounts. Required: icp, offer. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for outbound_sequencer: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Knowledge. Nothing to install.
outbound_sequencer is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the outbound_sequencer rule in your PolicyLayer 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 PolicyLayer policy for outbound_sequencer. 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.
outbound_sequencer is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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