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house / ElevenLabs + AutoMem Memory

✓ hosted skill bundlevoicev1.0.0MIT4.4 KB
skills/elevenlabs-automem-memory/SKILL.md

The safe integration shape for connecting an ElevenLabs conversational agent to a protected AutoMem MCP service.

InstallCLI + MCP
CLIRun from your local shell.
$autovault add jack-arturo/skillissue@775e1e1620d2730c8a67e8b7958448e3e888dfc2:skills/elevenlabs-automem-memory/SKILL.md --sync-profiles
MCPPaste into an agent MCP tool call.
>add_skill({ source: "github", identifier: "jack-arturo/skillissue@775e1e1620d2730c8a67e8b7958448e3e888dfc2:skills/elevenlabs-automem-memory/SKILL.md" })
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SKILL.mdview raw →
---
name: elevenlabs-automem-memory
description: Connect an ElevenLabs conversational agent to a protected AutoMem-compatible MCP service and verify that durable memory calls work in real conversations.
license: MIT
tags: [elevenlabs, automem, mcp, voice, deployment]
agents: [claude-code, codex, autojack]
category: voice
metadata:
  version: "1.0.0"
capabilities:
  network: true
  filesystem: readwrite
  tools: [Bash, Read, Edit]
requires-secrets:
  - name: ELEVENLABS_API_KEY
    description: API key for configuring the conversational agent.
    required: true
  - name: AUTOMEM_API_TOKEN
    description: Token used by the memory service and MCP bridge.
    required: true
resources:
  - path: story.md
    type: file
---

ElevenLabs + AutoMem Memory

Connect a conversational agent to an AutoMem-compatible service through an MCP

bridge. Treat memory as a production integration: isolate stores by persona,

keep credentials in the deployment platform's secret manager, and confirm the

real tool path before calling it done.

Preconditions

  • A supported memory API and MCP bridge are deployed and reachable.
  • The memory service has persistent storage appropriate for the provider.
  • The bridge requires an authorization header from clients; it must not fall back to an embedded upstream credential for anonymous requests.
  • ELEVENLABS_API_KEY and AUTOMEM_API_TOKEN are configured outside the repository. Never put either in a command, example file, or chat transcript.

Deploy the memory service

Use the provider's normal deployment controls. Configure public, non-secret

settings as environment variables and send secrets through its secret manager

or stdin-safe command. Names vary by implementation, but a typical boundary is:

MEMORY_API_URL=https://memory.example.com
MCP_BRIDGE_URL=https://memory-bridge.example.com/mcp
AUTOMEM_API_TOKEN=<managed secret>
EMBEDDING_API_KEY=<managed secret, if required>

Provision persistent database/vector storage according to the service's

documentation. Give each agent or persona a separate store and token unless a

shared-memory product decision explicitly says otherwise. Validate the API and

bridge health endpoints before configuring ElevenLabs.

Register the MCP server

Create an ElevenLabs conversational MCP server through the API or dashboard.

Use the bridge URL and send the token as an HTTP authorization header:

{
  "config": {
    "url": "https://memory-bridge.example.com/mcp",
    "name": "Agent Memory",
    "transport": "STREAMABLE_HTTP",
    "approval_policy": "require_approval_per_tool",
    "request_headers": {
      "Authorization": "Bearer ${AUTOMEM_API_TOKEN}"
    }
  }
}

Choose auto_approve_all only when the agent is intentionally autonomous and

the available tools have been reviewed. Otherwise, use per-tool approval and

permit only the calls the conversation needs. Do not put tokens in query

parameters: URLs are commonly logged by proxies and analytics systems.

Attach the returned MCP-server identifier to the agent's existing prompt

configuration. Fetch the configuration first and update it as a whole so a

partial patch cannot discard unrelated model, safety, or tool settings. Add a

short memory directive: recall relevant context when useful, store only durable

facts, and never expose stored memory as hidden system context.

Verify with a real conversation

Simulation endpoints can mock external tools, so they are useful for persona

checks but cannot prove a bridge call happened. Instead:

  1. Hold a real test conversation that should trigger a recall or store.
  2. Inspect that conversation's transcript or tool-call record in ElevenLabs.
  3. Confirm the expected MCP tool name and a successful result.
  4. Inspect the memory service's safe operational logs for a corresponding, redacted request.

If no tool call appears, verify the MCP server is attached to the active agent,

the agent is eligible for MCP use under its privacy/retention settings, the

authorization header reaches the bridge, and the bridge rejects missing tokens.

Security rules

  • Keep browser-accessible agent configuration free of API tokens.
  • Require a client token at the bridge; a health check is not evidence that authorization is enforced.
  • Use headers rather than query parameters for authentication.
  • Do not reuse one persona's memory token for another persona's store.
  • Rotate tokens through the secret manager and reconnect the bridge after a suspected exposure.
story.md

Why

Voice agents need continuity, but an MCP bridge is only useful when its access boundary is deliberate and testable.

How

Deploy a supported memory service using provider-managed environment variables, configure the MCP server with an authorization header, then verify tool calls from a real conversation.

Related

See AutoMem for memory discipline.

Bundle contents

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1files
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SKILL.md

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Declared capabilities

network
true
filesystem
readwrite
tools
[Bash, Read, Edit]

Requires: ELEVENLABS_API_KEY, AUTOMEM_API_TOKEN

Public, pinned, and inspectable

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package pin775e1e1sourceGitHub packagecompatibilityclaude-code, codex, autojack
VersionBundleSourcePinRaw
v1.0.0latest1 files · 4.4 KBhouse775e1e1SKILL.md