Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Voice operations — make phone calls (Bland AI), text-to-speech (ElevenLabs), transcribe audio (Whisper/Groq). Replace OpenClaw voice capabilities.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Voice interface commands. All API calls via curl — no SDK dependencies.
Credential resolution order: userConfig → env vars → Doppler MCP tools (mcp__doppler__*) → Doppler CLI fallback (doppler secrets get <KEY> --plain) → password manager
Parse $ARGUMENTS for the command keyword, then execute:
call [phone] [prompt] — Bland AI phone callRequires: bland_ai_api_key in userConfig or BLAND_AI_API_KEY env or Doppler.
BLAND_KEY="${BLAND_AI_API_KEY:-$(doppler secrets get BLAND_AI_API_KEY --plain 2>/dev/null || true)}"
PHONE="<extracted from $ARGUMENTS>"
PROMPT="<extracted from $ARGUMENTS or ask user>"
MAX_DURATION="${BLAND_MAX_DURATION:-300}" # seconds
VOICE="${BLAND_VOICE:-male}"
# Make the call
RESPONSE=$(curl -s -X POST "https://api.bland.ai/v1/calls" \
-H "authorization: $BLAND_KEY" \
-H "Content-Type: application/json" \
-d "{
\"phone_number\": \"$PHONE\",
\"task\": \"$PROMPT\",
\"voice\": \"$VOICE\",
\"max_duration\": $MAX_DURATION,
\"record\": true
}")
CALL_ID=$(echo "$RESPONSE" | python3 -c "import json,sys; print(json.load(sys.stdin).get('call_id',''))" 2>/dev/null)
# Poll for completion (up to 5 min)
if [ -n "$CALL_ID" ]; then
echo "Call initiated: $CALL_ID"
for i in $(seq 1 30); do
sleep 10
STATUS=$(curl -s "https://api.bland.ai/v1/calls/$CALL_ID" \
-H "authorization: $BLAND_KEY" | \
python3 -c "import json,sys; d=json.load(sys.stdin); print(d.get('status',''), d.get('transcripts','')[-1].get('text','') if d.get('transcripts') else '')" 2>/dev/null)
echo "Status: $STATUS"
[[ "$STATUS" == completed* ]] && break
done
fi
Output: Call ID, live status, transcript when complete.
tts [text] [--voice voice_id] [--out file.mp3] — ElevenLabs text-to-speechRequires: elevenlabs_api_key in userConfig or ELEVENLABS_API_KEY env or Doppler.
EL_KEY="${ELEVENLABS_API_KEY:-$(doppler secrets get ELEVENLABS_API_KEY --plain 2>/dev/null || true)}"
VOICE_ID="${ELEVENLABS_VOICE_ID:-21m00Tcm4TlvDq8ikWAM}" # Rachel (default)
TEXT="<extracted from $ARGUMENTS>"
OUT_FILE="${OUT_FILE:-/tmp/ops-tts-$(date +%s).mp3}"
# List voices if voice name provided (not an ID)
# Synthesize
curl -s -X POST "https://api.elevenlabs.io/v1/text-to-speech/${VOICE_ID}" \
-H "xi-api-key: $EL_KEY" \
-H "Content-Type: application/json" \
-d "{
\"text\": \"$TEXT\",
\"model_id\": \"eleven_monolingual_v1\",
\"voice_settings\": {\"stability\": 0.5, \"similarity_boost\": 0.75}
}" \
--output "$OUT_FILE"
echo "Audio saved to: $OUT_FILE"
# Auto-play on macOS
command -v afplay &>/dev/null && afplay "$OUT_FILE" &
Output: Audio file path. Auto-plays on macOS via afplay.
transcribe [file_path] — Groq Whisper transcriptionRequires: groq_api_key in userConfig or GROQ_API_KEY env or Doppler.
GROQ_KEY="${GROQ_API_KEY:-$(doppler secrets get GROQ_API_KEY --plain 2>/dev/null || true)}"
AUDIO_FILE="<extracted from $ARGUMENTS>"
if [ ! -f "$AUDIO_FILE" ]; then
echo "ERROR: File not found: $AUDIO_FILE"
exit 1
fi
TRANSCRIPT=$(curl -s -X POST "https://api.groq.com/openai/v1/audio/transcriptions" \
-H "Authorization: Bearer $GROQ_KEY" \
-F "file=@$AUDIO_FILE" \
-F "model=whisper-large-v3" \
-F "response_format=json" | \
python3 -c "import json,sys; print(json.load(sys.stdin).get('text',''))" 2>/dev/null)
echo "$TRANSCRIPT"
Output: Transcript text printed to stdout.
setup — Configure voice API keysBefore asking for anything, auto-scan ALL sources in a single background batch:
# Env vars
printenv BLAND_AI_API_KEY BLAND_API_KEY ELEVENLABS_API_KEY GROQ_API_KEY 2>/dev/null
# Shell profiles
grep -h 'BLAND\|ELEVENLABS\|GROQ' ~/.zshrc ~/.bashrc ~/.zprofile ~/.envrc 2>/dev/null | grep -v '^#'
# Doppler — ALL projects
for proj in $(doppler projects --json 2>/dev/null | jq -r '.[].slug'); do
for cfg in dev stg prd; do
doppler secrets --project "$proj" --config "$cfg" --json 2>/dev/null | \
jq -r --arg proj "$proj" --arg cfg "$cfg" 'to_entries[] | select(.key | test("BLAND|ELEVENLABS|GROQ"; "i")) | "\(.key)=\(.value.computed | .[0:12])... (doppler:\($proj)/\($cfg))"'
done
done
# Dashlane
dcli password bland --output json 2>/dev/null | jq -r '.[] | select(.password != null) | "\(.title): key found"'
dcli password elevenlabs --output json 2>/dev/null | jq -r '.[] | select(.password != null) | "\(.title): key found"'
dcli password groq --output json 2>/dev/null | jq -r '.[] | select(.password != null) | "\(.title): key found"'
# Keychain
security find-generic-password -s "bland-ai-api-key" -w 2>/dev/null
security find-generic-password -s "elevenlabs-api-key" -w 2>/dev/null
security find-generic-password -s "groq-api-key" -w 2>/dev/null
Present all findings. Only prompt for keys NOT found in any source. Then validate each found key in background:
curl -s -H "authorization: $KEY" https://api.bland.ai/v1/me — check balancecurl -s -H "xi-api-key: $KEY" https://api.elevenlabs.io/v1/voices?page_size=1 — list voicescurl -s -H "Authorization: Bearer $KEY" https://api.groq.com/openai/v1/models — list modelsReport: [service] ✓ connected or [service] ✗ invalid key — [error]
$ARGUMENTS (first word: call / tts / transcribe / setup)setup was not invoked, suggest /ops:ops-voice setupまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
日本語の概要は準備中です。原文の説明を表示しています。
Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
日本語の概要は準備中です。原文の説明を表示しています。
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
日本語の概要は準備中です。原文の説明を表示しています。
Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
日本語の概要は準備中です。原文の説明を表示しています。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。