abm_architect
Architecte ABM — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Gapup Hub — ABM 20 comptes nommés · Budget €120k · Tier 1×5 + Tier 2×15 · Playbooks 3 niveaux. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/abm-architect.md
What abm_architect does on Mcp Knowledge
AI agents call abm_architect to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
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 |
company | object | Yes | |
product | object | Yes | |
salesTeam | object | — | |
icpCriteria | array | Yes | |
abmBudgetEur | number | — | |
targetAccounts | array | Yes | |
currentChannels | array | — |
Parameters from the server's own tool schema.
Why abm_architect is rated Low
The tool appears to generate and return a structured analytical deliverable (ABM architecture plan) based on validated inputs. It reads/analyzes business parameters and produces a report or strategy document. There is no indication of writing to external systems, executing code, destructive actions, or financial transactions.
From the tool's definition 'Returns a structured, audited deliverable' and 'agent-payable C-suite expertise (CMO)' — generates structured ABM (Account-Based Marketing) strategy content/analysis based on inputs
Risk signalsHigh parameter count (21 properties)
Attacks that exploit this kind of access
The rule that runs abm_architect 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 abm_architect, this is the rule to start with:
abm_architect is read-only, so it stays allowed. 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 abm_architect call is checked against it from then on.
Questions about abm_architect
Architecte ABM — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Gapup Hub — ABM 20 comptes nommés · Budget €120k · Tier 1×5 + Tier 2×15 · Playbooks 3 niveaux. Inputs are validated server-side — send the documented case fields. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
abm_architect accepts 8 parameters: async, company, product, salesTeam, icpCriteria, abmBudgetEur, targetAccounts, currentChannels. Required: company, product, icpCriteria, targetAccounts. 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 abm_architect: 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.
abm_architect is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the abm_architect 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 abm_architect. 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.
abm_architect 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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