Ingest a voice/meeting transcript into the context memory. Converts pre-transcribed text (from Whisper, AssemblyAI, etc.) into a structured fragment capturing decisions, action items, open questions, technical vocabulary, and key discussion excerpts. Args: transcript: The full transcript text. so...
AI agents use ingest_voice to create or update resources in Entroly Context Engine — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Entroly Context Engine environment.
This tool writes structured data derived from a transcript into the context memory store. It creates/persists new records (decisions, actions, open questions, tech terms) in the system's memory. This is a Write operation — it stores data reversibly without executing code or deleting anything.
From the tool's definition Ingest a voice/meeting transcript into the context memory... Converts pre-transcribed text... into a structured fragment capturing decisions, action items, open questions, technical vocabulary
Documented attack patterns abuse exactly the kind of access ingest_voice gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Entroly Context Engine, and nothing reaches the server without passing your rules. This is the rule we recommend for ingest_voice:
{
"version": "1",
"default": "deny",
"tools": {
"ingest_voice": {
"limits": [
{
"counter": "ingest_voice_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}ingest_voice 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.
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Ingest a voice/meeting transcript into the context memory. Converts pre-transcribed text (from Whisper, AssemblyAI, etc.) into a structured fragment capturing decisions, action items, open questions, technical vocabulary, and key discussion excerpts. Args: transcript: The full transcript text. source: Identifier (e.g., 'design_meeting_2026-03-07.txt'). Returns JSON with ingestion result plus: - decisions, actions, open_questions (counts) - tech_terms_identified. It is categorised as a Write tool in the Entroly Context Engine MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Entroly Context Engine MCP server in PolicyLayer and add a rule for ingest_voice: 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 Entroly Context Engine. Nothing to install.
ingest_voice 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 ingest_voice 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 ingest_voice. 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.
ingest_voice is provided by the Entroly Context Engine MCP server (juyterman1000/entroly). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Entroly Context Engine, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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